Zilin Wang's starred repositories
CVPR2023-Papers-with-Code
CVPR 2023 论文和开源项目合集
Segment-Everything-Everywhere-All-At-Once
[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"
Deformable-DETR
Deformable DETR: Deformable Transformers for End-to-End Object Detection.
SupContrast
PyTorch implementation of "Supervised Contrastive Learning" (and SimCLR incidentally)
Semantic-SAM
[ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"
Awesome-Anything
General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX
awesome-segment-anything
Tracking and collecting papers/projects/others related to Segment Anything.
Personalize-SAM
Personalize Segment Anything Model (SAM) with 1 shot in 10 seconds
Semi-supervised-learning
A Unified Semi-Supervised Learning Codebase (NeurIPS'22)
vid2avatar
Vid2Avatar: 3D Avatar Reconstruction from Videos in the Wild via Self-supervised Scene Decomposition (CVPR2023)
segment-anything-fast
A batched offline inference oriented version of segment-anything
ICCV-2023-Papers
ICCV 2023 Papers: Discover cutting-edge research from ICCV 2023, the leading computer vision conference. Stay updated on the latest in computer vision and deep learning, with code included. ⭐ support visual intelligence development!
visual_anagrams
Code for the paper "Visual Anagrams: Generating Multi-View Optical Illusions with Diffusion Models"
Awesome-Segment-Anything
This repository is for the first comprehensive survey on Meta AI's Segment Anything Model (SAM).
awesome-robotics-datasets
A collection of useful datasets for robotics and computer vision
sim-web-visualizer
Web Based Visualizer for Simulation Environments
self-mono-sf
Self-Supervised Monocular Scene Flow Estimation (CVPR 2020)
object_localization_network
Learning Open-World Object Proposals without Learning to Classify
RCF-UnsupVideoSeg
[CVPR 2023] Segmenting objects in videos without human annotations 🤯: Official implementation for Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping