TianpengBu

objectdetection-saliency-maps

Based on the mmdetection framework, compute various salience maps for object detection.

devit

MQ-Det

Official PyTorch implementation of "Multi-modal Queried Object Detection in the Wild" (accepted by NeurIPS 2023)

GroundingDINO

[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"

scenic

Scenic: A Jax Library for Computer Vision Research and Beyond

OvarNet

OvarNet official implement of the paper "OvarNet: Towards Open-vocabulary Object Attribute Recognition"

all-seeing

[ICLR 2024] This is the official implementation of the paper "The All-Seeing Project: Towards Panoptic Visual Recognition and Understanding of the Open World"

viper

Code for the paper "ViperGPT: Visual Inference via Python Execution for Reasoning"

deeplite-torch-zoo

Collection of SOTA efficient computer vision models for embedded applications, with pre-trained weights and training recipes

FastSAM

Fast Segment Anything

bolei_awesome_posters

CVPR and NeurIPS poster examples and templates. May we have in-person poster session soon!

ChatCaptioner

Official Repository of ChatCaptioner

GRiT

GRiT: A Generative Region-to-text Transformer for Object Understanding (https://arxiv.org/abs/2212.00280)

Caption-Anything

Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences. https://huggingface.co/spaces/TencentARC/Caption-Anything https://huggingface.co/spaces/VIPLab/Caption-Anything

LAVIS

LAVIS - A One-stop Library for Language-Vision Intelligence

VLM_survey

Collection of AWESOME vision-language models for vision tasks

MultiModal_BigModels_Survey

[MIR-2023-Survey] A continuously updated paper list for multi-modal pre-trained big models

Awesome-Controllable-Generation

Papers and resources on Controllable Generation using Diffusion Models, including ControlNet, DreamBooth, T2I-Adapter, IP-Adapter.

MI-AOD

Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

mmdetection-mini

mmdetection最小学习版

nanodet

NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥

awesome-grounding

awesome grounding: A curated list of research papers in visual grounding

awesome-yolo-object-detection

🚀🚀🚀 A collection of some awesome public YOLO object detection series projects.

GLIP

Grounded Language-Image Pre-training

tf-keras-vis

Neural network visualization toolkit for tf.keras

DANet

Dual Attention Network for Scene Segmentation (CVPR2019)

FastestDet

:zap: A newly designed ultra lightweight anchor free target detection algorithm， weight only 250K parameters， reduces the time consumption by 10% compared with yolo-fastest, and the post-processing is simpler

YOLOX-Lite

将YOLOv5-Lite代码中的head更换为YOLOX head

YOLOv5-Lite

🍅🍅🍅YOLOv5-Lite: Evolved from yolov5 and the size of model is only 900+kb (int8) and 1.7M (fp16). Reach 15 FPS on the Raspberry Pi 4B~

awesome-tiny-object-detection

🕶 A curated list of Tiny Object Detection papers and related resources.