Pinned Repositories
detrex
detrex is a research platform for DETR-based object detection, segmentation, pose estimation and other visual recognition tasks.
Grounded-SAM-2
Grounded SAM 2: Ground and Track Anything in Videos with Grounding DINO, Florence-2 and SAM 2
Grounded-Segment-Anything
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Grounding-DINO-1.5-API
API for Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series
GroundingDINO
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
pytorch-distributed-training
Simple tutorials on Pytorch DDP training
pytorch-pooling
Test different pooling method used in CNN for Computer Vision Task
TRAR-VQA
[ICCV 2021] Official implementation of the paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering"
visualization
a collection of visualization function
ViT.pytorch
The Pytorch reimplementation of Vision Transformer
rentainhe's Repositories
rentainhe/Learn-Detectron2-From-Scratch
Detectron2 Learning Notes Sharing
rentainhe/knowledge-graph-visualization
knowledge graph system based on Neo4j and Vue
rentainhe/rentainhe.github.io
Personal homepage
rentainhe/Awesome-Anything
General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX
rentainhe/MambaOut
MambaOut: Do We Really Need Mamba for Vision?
rentainhe/ollama
Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
rentainhe/sam2
The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
rentainhe/Caption-Anything
Caption-Anything is a versatile tool combining image segmentation, visual captioning, and ChatGPT, generating tailored captions with diverse controls for user preferences.
rentainhe/dataset-api
The ApolloScape Open Dataset for Autonomous Driving and its Application.
rentainhe/detectron2
Detectron2 is FAIR's next-generation platform for object detection, segmentation and other visual recognition tasks.
rentainhe/DiffusionDet
PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788)
rentainhe/DINO
[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"
rentainhe/DiT
Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"
rentainhe/EVA
Exploring the Limits of Masked Visual Representation Learning at Scale (https://arxiv.org/abs/2211.07636)
rentainhe/GroundingDINO
The official implementation of "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
rentainhe/InternImage
[CVPR 2023] InternImage: Exploring Large-Scale Vision Foundation Models with Deformable Convolutions
rentainhe/InternVL
[CVPR 2024 Oral] InternVL Family: A Pioneering Open-Source Alternative to GPT-4o. 接近GPT-4o表现的可商用开源多模态对话模型
rentainhe/learn-ddim
Denoising Diffusion Implicit Models
rentainhe/learned-guided-diffusion
Learning Guided Diffusion
rentainhe/object-intrinsics
(CVPR 2023) Seeing a Rose in Five Thousand Ways
rentainhe/OpenSeeD
[ICCV 2023] Official implementation of the paper "A Simple Framework for Open-Vocabulary Segmentation and Detection"
rentainhe/pytorch-image-models
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
rentainhe/Qwen-VL
The official repo of Qwen-VL (通义千问-VL) chat & pretrained large vision language model proposed by Alibaba Cloud.
rentainhe/Qwen2
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud.
rentainhe/rentainhe
rentainhe/segment-anything
The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
rentainhe/Segment-Everything-Everywhere-All-At-Once
Official implementation of the paper "Segment Everything Everywhere All at Once"
rentainhe/stable-diffusion
rentainhe/stable-diffusion-learned
Personal Learning Version
rentainhe/T-Rex
Detect and count any objects by visual prompting