ZHUXUHAN / Structured-Sparse-RCNN

[CVPR 2022] Structured Sparse R-CNN for Direct Scene Graph Generation

Structured Sparse R-CNN for Direct Scene Graph Generation

Our paper Structured Sparse R-CNN for Direct Scene Graph Generation has been accepted by CVPR 2022.

Requirements

Environments: python 3.8, cuda 10.1, pytorch 1.7.1

To install requirements:

conda create --name scene_graph_benchmark
conda activate scene_graph_benchmark

pip install --user ipython
pip install --user scipy
pip install --user h5py
pip install --user pyyaml
pip install --user yacs
pip install --user scipy
pip install --user h5py
pip install --user tqdm
pip install --user opencv-python

pip install --user ninja yacs cython matplotlib tqdm opencv-python overrides


conda install pytorch==1.7.1 torchvision==0.8.2 cudatoolkit=10.1 -c pytorch

git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
python setup.py build_ext install

git clone https://github.com/NVIDIA/apex.git
cd apex
python setup.py install --cuda_ext --cpp_ext

# put our code SGGbench into your directory, such as /home/username
cd /home/username/SGGbench 
python setup.py build develop

Datasets

VG

For the dataset and pretrained backbone weights preparation, please follow: Scene-Graph-Benchmark.pytorch

OI v4, v6

For the datasets and pretrained backbone weights preparation, please follow: BGNN-SGG. Actually, BGNN-SGG is also compatible with Scene-Graph-Benchmark.pytorch.

Training

VG

To train the model with 300 triplet queries in the paper, run this command: (8 RTX 2080ti 11G)

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_train_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.PRETRAINED_DETECTOR_CKPT checkpoints/pretrained_faster_rcnn/model_final.pth OUTPUT_DIR Outputs/real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

To train the model with 800 triplet queries in the paper, run this command: (8 V100 32G)

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_train_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.PRETRAINED_DETECTOR_CKPT checkpoints/pretrained_faster_rcnn/model_final.pth OUTPUT_DIR Outputs/real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 800 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

OI V4

To train the model with 300 triplet queries in the paper, run this command: (8 RTX 2080ti 11G)

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_train_net.py --config-file "configs/oiv4_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.PRETRAINED_DETECTOR_CKPT checkpoints/iov4_pretrain_faster_rcnn/model_final.pth OUTPUT_DIR Outputs/oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

OI V6

To train the model with 300 triplet queries in the paper, run this command: (8 RTX 2080ti 11G)

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_train_net.py --config-file "configs/oiv6_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.PRETRAINED_DETECTOR_CKPT checkpoints/iov6_pretrain_faster_rcnn/model_final.pth OUTPUT_DIR Outputs/oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

Evaluation

VG

300 queries

To evaluate my model, run:

CUDA_VISIBLE_DEVICES=4,5,6,7 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/eva_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'eva_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with TDE, run:

CUDA_VISIBLE_DEVICES=2,3,4,5 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/tde_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS True MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'tde_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with our LA, run:

CUDA_VISIBLE_DEVICES=4,5,6,7 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/la03_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True MODEL.SimrelRCNN.REL_LOGITS_ADJUSTMENT True MODEL.SimrelRCNN.LOGIT_ADJ_TAU 0.3

📋 Before testing, create a new directory, named 'la03_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

800 queries

To evaluate my model, run:

CUDA_VISIBLE_DEVICES=3,5,6,7 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/eva_real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 800 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'eva_real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with TDE, run:

CUDA_VISIBLE_DEVICES=2,3,4,5 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/tde_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 800 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS True MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'tde_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with our LA, run:

CUDA_VISIBLE_DEVICES=3,5,6,7 python -m torch.distributed.launch --master_port 10029 --nproc_per_node=4 tools/relation_test_net.py --config-file "configs/simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 4 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/LA03_real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 800 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 256 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True MODEL.SimrelRCNN.REL_LOGITS_ADJUSTMENT True MODEL.SimrelRCNN.LOGIT_ADJ_TAU 0.3

📋 Before testing, create a new directory, named 'LA03_real025kl_newe2rposition_fullobjbranch_800q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

OI V4

300 queries

To evaluate my model, run:

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_test_net.py --config-file "configs/oiv4_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/eva_oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'eva_oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with our LA, run:

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_test_net.py --config-file "configs/oiv4_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/la_oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True MODEL.SimrelRCNN.REL_LOGITS_ADJUSTMENT True MODEL.SimrelRCNN.LOGIT_ADJ_TAU 0.3

📋 Before testing, create a new directory, named 'la_oiv4_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

OI V6

300 queries

To evaluate my model, run:

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_test_net.py --config-file "configs/oiv6_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/eva_oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True

📋 Before testing, create a new directory, named 'eva_oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

To evaluate my model with our LA, run:

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python -m torch.distributed.launch --master_port 10020 --nproc_per_node=8 tools/relation_test_net.py --config-file "configs/oiv6_simrel_e2e_relation_X_101_32_8_FPN_1x.yaml" MODEL.ROI_RELATION_HEAD.USE_GT_BOX False MODEL.ROI_RELATION_HEAD.USE_GT_OBJECT_LABEL False MODEL.ROI_RELATION_HEAD.PREDICTOR CausalAnalysisPredictor MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_TYPE none MODEL.ROI_RELATION_HEAD.CAUSAL.FUSION_TYPE sum MODEL.ROI_RELATION_HEAD.CAUSAL.CONTEXT_LAYER motifs SOLVER.IMS_PER_BATCH 8 TEST.IMS_PER_BATCH 8 SOLVER.VAL_PERIOD 12000 SOLVER.MAX_ITER 80000 SOLVER.STEPS '(47000, 64000)' SOLVER.BASE_LR 0.000008 SOLVER.OPTIMIZER "ADAMW" MODEL.WEIGHT Outputs/oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel/model_final.pth OUTPUT_DIR Outputs/la_oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel MODEL.ROI_BOX_HEAD.MLP_HEAD_DIM 1024 MODEL.SimrelRCNN.ENABLE_BG_OBJ False MODEL.SimrelRCNN.ENABLE_REL_X2Y True MODEL.SimrelRCNN.REL_DIM 256 MODEL.SimrelRCNN.NUM_PROPOSALS 300 MODEL.SimrelRCNN.NUM_HEADS 6 MODEL.SimrelRCNN.REL_STACK_NUM 6 MODEL.SimrelRCNN.TRIPLET_MASK_WEIGHT 1.0 MODEL.SimrelRCNN.FREEZE_BACKBONE True MODEL.SimrelRCNN.CROSS_OBJ_FEAT_FUSION False MODEL.SimrelRCNN.CLASS_WEIGHT 1.333 MODEL.SimrelRCNN.L1_WEIGHT 5.0 MODEL.SimrelRCNN.GIOU_WEIGHT 2.0 GLOVE_DIR '' MODEL.SimrelRCNN.ENABLE_FREQ False MODEL.SimrelRCNN.ENABLE_QUERY_REVERSE False MODEL.SimrelRCNN.USE_REFINE_OBJ_FEATURE True MODEL.SimrelRCNN.FREEZE_PUREE_OBJDET False MODEL.SimrelRCNN.PURE_ENT_NUM_PROPOSALS 100 MODEL.SimrelRCNN.ENABLE_MASK_BRANCH False MODEL.SimrelRCNN.KL_BRANCH_WEIGHT 0.25 MODEL.SimrelRCNN.ENABLE_KL_BRANCH True MODEL.SimrelRCNN.POSI_ENCODE_DIM 64 MODEL.SimrelRCNN.REL_CLASS_WEIGHT 1.334 MODEL.SimrelRCNN.PURE_ENT_CLASS_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_GIOU_WEIGHT 2.0 MODEL.SimrelRCNN.PURE_ENT_L1_WEIGHT 5.0 MODEL.SimrelRCNN.AUXILIARY_BRANCH True MODEL.SimrelRCNN.AUXILIARY_BRANCH_SELECT_ENT_MAX_NUM 25 MODEL.SimrelRCNN.AUXILIARY_BRANCH_START 11 MODEL.SimrelRCNN.ENABLE_ENT_PROP True MODEL.ROI_RELATION_HEAD.CAUSAL.EFFECT_ANALYSIS False MODEL.SimrelRCNN.USE_CROSS_RANK False MODEL.SimrelRCNN.DISABLE_KQ_FUSION_SELFATTEN False MODEL.SimrelRCNN.DIM_ENT_PRE_CLS 1024 MODEL.SimrelRCNN.DIM_ENT_PRE_REG 256 MODEL.SimrelRCNN.ONE_REL_CONV True MODEL.SimrelRCNN.ENABLE_BATCH_REDUCTION True MODEL.SimrelRCNN.USE_HARD_LABEL_KLMATCH True MODEL.SimrelRCNN.DISABLE_OBJ2REL_LOSS True MODEL.SimrelRCNN.REL_LOGITS_ADJUSTMENT True MODEL.SimrelRCNN.LOGIT_ADJ_TAU 0.3

📋 Before testing, create a new directory, named 'la_oiv6_real025kl_newe2rposition_fullobjbranch_300q_smalldyconv_prequeryaug9_norel_hardlabel', in ./SGGbench/Outputs/ .

Pre-trained Models

You can download pretrained models here:

VG

300 queries

800 queries

OI V4

300 queries

OI V6

300 queries

Results

Our model achieves the following performance on :

Visual Genome

* means 800 queries.

Models	SGGen R@20	SGGen R@50	SGGen R@100	SGGen zR@20	SGGen zR@50	SGGen zR@100	SGGen mR@20	SGGen mR@50	SGGen mR@100
Our model	25.8	32.7	36.9	1.5	2.7	3.7	6.1	8.4	10.0
Our model*	26.1	33.5	38.4	1.5	2.7	4.0	6.2	8.6	10.3
Our model+TDE	14.5	18.3	21.0	1.8	2.7	3.6	10.8	15.0	18.5
Our model*+TDE	15.0	19.7	22.9	1.6	2.7	3.8	9.8	14.6	18.0
Our model+LA	18.4	23.3	26.5	1.9	2.9	4.0	13.5	17.9	21.4
Our model*+LA	18.2	23.7	27.3	2.0	3.1	4.5	13.7	18.6	22.5

Acknowledgement

Our code is mainly based on: Scene-Graph-Benchmark.pytorch, SparseR-CNN and BGNN-SGG.

For this paper, I'm extremely grateful to my advisor Prof. Limin Wang. I should also appreciate my group members for discussing with me: Jing Tan, Ziteng Gao and Jiaqi Tang.

Citations

@inproceedings{ssrcnnsgg22cvpr,
  author    = {Yao Teng and
               Limin Wang},
  title     = {Structured Sparse {R-CNN} for Direct Scene Graph Generation},
  booktitle = {{CVPR}},
  year      = {2022}
}