ZhangJin's repositories
Attention-Guided-Contextual-Feature-Fusion-Network-for-Salient-Object-Detection
This repo. is an implementation of ACFFNet, which is accepted for in Image and Vision Computing.
SOD-CNNs-based-code-summary-
The summary of code and paper for salient object detection with deep learning
doubly-contrastive-semseg
Doubly Contrastive End-to-End Semantic Segmentation for Autonomous Driving under Adverse Weather (BMVC 2022)
awesome-DeepLearning
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
ConvNeXt
Code release for ConvNeXt model
DCFM
official repository for "Democracy Does Matter: Comprehensive Feature Mining for Co-salient Object Detection" --accepted by CVPR2022
LEDNet
PyTorch codes for "LEDNet: Joint Low-light Enhancement and Deblurring in the Dark" (ECCV2022)
Machine-Learning-notes
A series of notes of the formula derivation of ML
MonoDepth-FPN-PyTorch
Single Image Depth Estimation with Feature Pyramid Network
Paddle
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
PaddleSeg
End-to-end image segmentation kit based on PaddlePaddle.
ProtoKD
[ICASSP 2023] Prototype Knowledge Distillation for Medical Segmentation with Missing Modality
PSOD
Point Saliency
PyTorch-Lightning_Template_for_Semantic_Segmentation
Pytorch Lightning Template for Sematic Segmentation
QPT
[内测中]前向式Python环境快捷封装工具,快速将Python打包为EXE并添加CUDA、NoAVX等支持。
RAS_python
Pytorch realization for "Reverse Attention for Salient Object Detection": ECCV2018.
RefCOD
Official Code for 'Referring Camouflaged Object Detection (指向性伪装物体检测) '
SOCToolbox
Efficient Toolbox to quickly evaluate SOC/SOD/COD benchmark.
TRACER
TRACER: Extreme Attention Guided Salient Object Tracing Network (AAAI 2022) implementation in PyTorch
UDASOD-UPL
Unsupervised Domain Adaptive Salient Object Detection Through Uncertainty-Aware Pseudo-Label Learning, AAAI Conference on Artificial Intelligence (AAAI), 2022
v2x-vit
[ECCV2022] Official Implementation of paper "V2X-ViT: Vehicle-to-Everything Cooperative Perception with Vision Transformer"