gasharper

gasharper's Stars

• youngyangyang04/leetcode-master

  《代码随想录》LeetCode 刷题攻略：200道经典题目刷题顺序，共60w字的详细图解，视频难点剖析，50余张思维导图，支持C++，Java，Python，Go，JavaScript等多语言版本，从此算法学习不再迷茫！🔥🔥 来看看，你会发现相见恨晚！🚀

  Language:Shell52.2k38224111.6k

• ultralytics/ultralytics

  Ultralytics YOLO11 🚀

  Language:Python32.9k1839.5k6.3k

• facebookresearch/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.

  Language:Jupyter Notebook12.5k723651.2k

• liguodongiot/llm-action

  本项目旨在分享大模型相关技术原理以及实战经验（大模型工程化、大模型应用落地）

  Language:HTML10.9k95221.1k

• facebookresearch/pytorch3d

  PyTorch3D is FAIR's library of reusable components for deep learning with 3D data

  Language:Python8.8k1491.6k1.3k

• IDEA-Research/GroundingDINO

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

  Language:Python6.8k42305689

• pengsida/learning_research

  本人的科研经验

  6k7228354

• AILab-CVC/YOLO-World

  [CVPR 2024] Real-Time Open-Vocabulary Object Detection

  Language:Python4.7k39462456

• cambrian-mllm/cambrian

  Cambrian-1 is a family of multimodal LLMs with a vision-centric design.

  Language:Python1.8k2169115

• real-stanford/diffusion_policy

  [RSS 2023] Diffusion Policy Visuomotor Policy Learning via Action Diffusion

  Language:Python1.6k18105325

• hkchengrex/Tracking-Anything-with-DEVA

  [ICCV 2023] Tracking Anything with Decoupled Video Segmentation

  Language:Python1.3k16110129

• HuangOwen/Awesome-LLM-Compression

  Awesome LLM compression research papers and tools.

  1.2k42479

• minghanqin/LangSplat

  Official implementation of the paper "LangSplat: 3D Language Gaussian Splatting" [CVPR2024 Highlight]

  Language:Python679206772

• zju3dv/EfficientLoFTR

  Language:Jupyter Notebook628385047

• Tsingularity/dift

  [NeurIPS'23] Emergent Correspondence from Image Diffusion

  Language:Python61972535

• yoxu515/aot-benchmark

  An efficient modular implementation of Associating Objects with Transformers for Video Object Segmentation in PyTorch

  Language:Python6084682108

• robocasa/robocasa

  RoboCasa: Large-Scale Simulation of Everyday Tasks for Generalist Robots

  Language:Python574119447

• shenyunhang/APE

  [CVPR 2024] Aligning and Prompting Everything All at Once for Universal Visual Perception

  Language:Python48986229

• longzw1997/Open-GroundingDino

  This is the third party implementation of the paper Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

  Language:Python43438769

• Nightmare-n/DepthAnyVideo

  Depth Any Video with Scalable Synthetic Data

  Language:Python404201926

• zhangzjn/ADer

  ADer (https://arxiv.org/abs/2406.03262) is an open source visual anomaly detection toolbox based on PyTorch, which supports multiple popular AD datasets and approaches.

  Language:Python18842813

• merveenoyan/siglip

  Projects based on SigLIP (Zhai et. al, 2023) and Hugging Face transformers integration 🤗

  Language:Jupyter Notebook1443210

• Z-Zheng/pytorch-change-models

  torchange - A Unified Change Representation Learning Benchmark Library

  Language:Python77423

• Curt-Park/yolo-world-with-efficientvit-sam

  YOLO-World + EfficientViT SAM

  Language:Python76219

• hnuzhy/CV_DL_Gather

  Gather research papers, corresponding codes (if having), reading notes and any other related materials about Hot🔥🔥🔥 fields in Computer Vision based on Deep Learning.

  61706

• Asad-Ismail/Grounding-Dino-FineTuning

  Fine tuning grounding Dino

  Language:Python59368

• hkchengrex/Grounded-Segment-Anything

  Grounded-SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

  Language:Jupyter Notebook381010

• jiaosiyu1999/MAFT-Plus

  Language:Python31285

• ragavsachdeva/CYWS-3D

  The official implementation of the paper The Change You Want to See (Now in 3D) (ICCVW 2023).

  Language:Python20263

• FlagOpen/Awesome-Industry-Dataset

  旨在收集各行业的开源数据，引导和推动行业大模型的发展

  161