we4237
Follow
Lists (5)
Stars
A fix for Metaphor: ReFantazio that adds ultrawide/narrower support and much more.
[ACM-MM'24 Oral] PASSION: Towards Effective Incomplete Multi-Modal Medical Image Segmentation with Imbalanced Missing Rates
[NeurIPS 2023] SimMMDG: A Simple and Effective Framework for Multi-modal Domain Generalization
BoxMOT: pluggable SOTA tracking modules for segmentation, object detection and pose estimation models
[ICML 2024] Official repository of the paper: "Diving into Underwater: Segment Anything Model Guided Underwater Salient Instance Segmentation and A Large-scale Dataset"
小红书笔记 | 评论爬虫、抖音视频 | 评论爬虫、快手视频 | 评论爬虫、B 站视频 ｜ 评论爬虫、微博帖子 ｜ 评论爬虫、百度贴吧帖子 ｜ 百度贴吧评论回复爬虫 | 知乎问答文章｜评论爬虫
Tool to backup your saves and view your world rolls
NVIDIA TensorRT deployment of Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data.
One-step image-to-image with Stable Diffusion turbo: sketch2image, day2night, and more
Codes for "A Benchmarking Protocol for SAR Colorization: From Regression to Deep Learning Approaches"
Rethinking Multi-domain Generalization with A General Learning Objective, accepted by cvpr24
Pointers to large-scale underwater datasets and relevant resources.
[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation
U-shape Transformer for Underwater Image Enhancement
[CVPR 2022] Official Pytorch code for OW-DETR: Open-world Detection Transformer
Implementation of paper - YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information
Convert JSON annotations into YOLO format.
source code for ICLR'22 paper "VOS: Learning What You Don’t Know by Virtual Outlier Synthesis"
[CVPR 2023] Official Pytorch code for Unknown Sniffer for Object Detection: Don’t Turn a Blind Eye to Unknown Objects
A list of papers that studies Novel Class Discovery
Novel Visual Category Discovery with Dual Ranking Statistics and Mutual Knowledge Distillation. Bingchen Zhao and Kai Han. (NeurIPS 2021)
The Official Repository for "Generalized OOD Detection: A Survey"
A PyTorch implementation of Deep SAD, a deep Semi-supervised Anomaly Detection method.
Deep SAD model with customized datasets. Source: https://github.com/lukasruff/Deep-SAD-PyTorch
An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.