Stars
Offical Code of MICCAI'24 early accepted paper "LGRNet: Local-Global Reciprocal Network for Uterine Fibroid Segmentation in Ultrasound Videos"
The implementation of the paper “Generalize Polyp Segmentation via Inpainting across Diverse Backgrounds and Pseudo-Mask Refinement”
(IJCV2024 & ICCV2023) LSKNet: A Foundation Lightweight Backbone for Remote Sensing
The official implementation of VLPL: Vision Language Pseudo Label for Multi-label Learning with Single Positive Labels
📜 [CVPRw] SAM-PM: Enhancing Video Camouflaged Object Detection using Spatio-Temporal Attention, Muhammad Nawfal Meeran, Gokul Adethya T, Bhanu Pratyush Mantha
PySODMetrics: A Simple and Efficient Implementation of Grayscale/Binary Segmentation Metrcis
(ICML 2024) Spider: A Unified Framework for Context-dependent Concept Segmentation
[CVPR 2024] Adaptive Fusion of Single-View and Multi-View Depth for Autonomous Driving
PyTorch-Based Evaluation Tool for Co-Saliency Detection
Mutual Information Regularization for Weakly-supervised RGB-D Salient Object Detection
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
Pointers to a collection of underwater image-based datasets and relevant resources.
Single Underwater Image Enhancement and Color Restoration, which is Python implementation for a comprehensive review paper "An Experimental-based Review of Image Enhancement and Image Restoration M…
Pointers to large-scale underwater datasets and relevant resources.
Shifting More Attention to Video Salient Objection Detection, CVPR 2019 (Best Paper Finalist)
Paper list for single object tracking (State-of-the-art SOT trackers)
PyTorch implementation of SimSiam https//arxiv.org/abs/2011.10566
Adapting Meta AI's Segment Anything to Downstream Tasks with Adapters and Prompts
A comprehensive list of awesome contrastive self-supervised learning papers.
Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"