Stars
This is an official PyTorch implementation for "MuSc : Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images" (MuSc ICLR2024).
[IEEE TITS] Exploiting Low-level Representations for Ultra-Fast Road Segmentation
This is the official code for MobileSAM project that makes SAM lightweight for mobile applications and beyond!
Official code for RbA: Segmenting Unknown Regions Rejected by All (ICCV 2023)
General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX
[ECCV 2024] Official implementation of the paper "Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection"
[ICCV'23 Oral] Unmasking Anomalies in Road-Scene Segmentation
[ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch
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.
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
[TPAMI 2025 & CVPR 2023] Iterative Geometry Encoding Volume for Stereo Matching
A novel neural network architecture that can concurrently achieve real-time performance, competitive accuracy, and strong generalization ability.
[TPAMI 2024] Fast-ACV: Fast Attention Concatenation Volume for Accurate and Real-time Stereo Matching
[NeurIPS 2022 Spotlight] GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models
[ICCV'23] Residual Pattern Learning for Pixel-wise Out-of-Distribution Detection in Semantic Segmentation
Scaling Up Your Kernels to 31x31: Revisiting Large Kernel Design in CNNs (CVPR 2022)
[MICCAI 2022] Dual-Distribution Discrepancy for Anomaly Detection in Chest X-Rays
Detecting Anomalies in Semantic Segmentation with Prototypes
[TPAMI 2024 & CVPR 2022] Attention Concatenation Volume for Accurate and Efficient Stereo Matching
This repository provides the PyTorch implementation of the paper: Anomaly Discovery in Semantic Segmentation via Distillation Comparison Networks
[ICCV 2021] Deep Metric Learning for Open World Semantic Segmentation