yztongzhan

yztongzhan's Stars

• facebookresearch/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.

  Language:Jupyter Notebook45.2k2996505.3k

• XingangPan/DragGAN

  Official Code for DragGAN (SIGGRAPH 2023)

  Language:Python35.3k1k1853.4k

• meta-llama/codellama

  Inference code for CodeLlama models

  Language:Python15.4k1761901.8k

• NVIDIA/open-gpu-kernel-modules

  NVIDIA Linux open GPU kernel module source

  Language:C14.2k1723181.2k

• qiuyu96/CoDeF

  [CVPR 2024 Highlight] Official PyTorch implementation of CoDeF: Content Deformation Fields for Temporally Consistent Video Processing

  Language:Python4.8k7479389

• OpenGVLab/InternGPT

  InternGPT (iGPT) is an open source demo platform where you can easily showcase your AI models. Now it supports DragGAN, ChatGPT, ImageBind, multimodal chat like GPT-4, SAM, interactive image editing, etc. Try it at igpt.opengvlab.com (支持DragGAN、ChatGPT、ImageBind、SAM的在线Demo系统)

  Language:Python3.2k4349229

• TigerResearch/TigerBot

  TigerBot: A multi-language multi-task LLM

  Language:Python2.2k31125194

• ShoufaChen/DiffusionDet

  [ICCV2023 Best Paper Finalist] PyTorch implementation of DiffusionDet (https://arxiv.org/abs/2211.09788)

  Language:Python2k17112155

• fenglinglwb/MAT

  MAT: Mask-Aware Transformer for Large Hole Image Inpainting

  Language:Python7171111379

• OpenGVLab/VideoMAEv2

  [CVPR 2023] VideoMAE V2: Scaling Video Masked Autoencoders with Dual Masking

  Language:Python44165143

• tinatiansjz/hmr-survey

  [TPAMI 2023] Recovering 3D Human Mesh from Monocular Images: A Survey

  33315511

• ShoufaChen/AdaptFormer

  [NeurIPS 2022] Implementation of "AdaptFormer: Adapting Vision Transformers for Scalable Visual Recognition"

  Language:Python30573517

• MCG-NJU/SparseBEV

  [ICCV 2023] SparseBEV: High-Performance Sparse 3D Object Detection from Multi-Camera Videos

  Language:Python30397720

• chaytonmin/Occupancy-MAE

  Official implementation of our TIV'23 paper: Occupancy-MAE: Self-supervised Pre-training Large-scale LiDAR Point Clouds with Masked Occupancy Autoencoders

  Language:Python24173020

• implus/UM-MAE

  Official Codes for "Uniform Masking: Enabling MAE Pre-training for Pyramid-based Vision Transformers with Locality"

  Language:Jupyter Notebook23452220

• fenglinglwb/EDT

  On Efficient Transformer-Based Image Pre-training for Low-Level Vision

  Language:Python12714118

• MCG-NJU/SportsMOT

  [ICCV 2023] SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenes

  Language:Python1225154

• AILab-CVC/GroupMixFormer

  GroupMixAttention and GroupMixFormer

  Language:Python1079411

• zhaoyue-zephyrus/AVION

  Code release for "Training a Large Video Model on a Single Machine in a Day"

  Language:Python991104

• zhaoyue-zephyrus/TeSTra

  Code for ECCV2022 "Real-time Online Video Detection with Temporal Smoothing Transformers"

  Language:Python942117

• ChongjianGE/MetaBEV

  MetaBEV: Solving Sensor Failures for BEV Detection and Map Segmentation

  86666

• showlab/sparseformer

  (ICLR 2024, CVPR 2024) SparseFormer

  Language:Python61931

• MCG-NJU/DDM

  [CVPR 2022] Progressive Attention on Multi-Level Dense Difference Maps for Generic Event Boundary Detection

  Language:Python472103

• MCG-NJU/STMixer

  [CVPR 2023] STMixer: A One-Stage Sparse Action Detector

  Language:Python47144

• MCG-NJU/VideoMAE-Action-Detection

  [NeurIPS 2022 Spotlight] VideoMAE for Action Detection

  Language:Python46263

• MCG-NJU/EVAD

  [ICCV 2023] Efficient Video Action Detection with Token Dropout and Context Refinement

  Language:Python20243

• leexinhao/ZeroI2V

  Official implementation of "ZeroI2V: Zero-Cost Adaptation of Pre-trained Transformers from Image to Video"

  Language:Python13370

• ChongjianGE/SNCLR

  [ICLR 2023] Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning

  Language:Python11221

• sebgao/chatgpt_mini_helper

  My customized GPT 3.5 helper

  Language:Python7201

• yztongzhan/VideoMAE

  VideoMAE: Masked Autoencoders are Data-Efficient Learners for Self-Supervised Video Pre-Training

  Language:Python1100