Stars
official code of "Noise-Aware Adaptation of Pre-trained Foundation Models for Single-photon Image Classification"
Pointcept: Perceive the world with sparse points, a codebase for point cloud perception research. Latest works: Concerto (NeurIPS'25), Sonata (CVPR'25 Highlight), PTv3 (CVPR'24 Oral)
text and visual prompt for habitat image labeling via CLIP
Establishing grid map based on radar measurement
A PyTorch converter for SimCLR checkpoints
Application of SymmNet UDA and scaling to improve benthic classification.
An implementation of the state-of-the-art Deep Active Learning algorithms
PyTorch implementation of EMAN for self-supervised and semi-supervised learning: https://arxiv.org/abs/2101.08482
Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.
Active Learning on a Budget - Opposite Strategies Suit High and Low Budgets
A PyTorch-based library for semi-supervised learning (NeurIPS'21)
[CVPR 2022] Pytorch implementation for “Debiased Learning from Naturally Imbalanced Pseudo-Labels”
Toolbox of models, callbacks, and datasets for AI/ML researchers.
The code for paper 'Hierarchical Policy for Non-prehensile Multi-object Rearrangement with Deep Reinforcement Learning and Monte Carlo Tree Search'
Code for Deterministic Neural Networks with Appropriate Inductive Biases Capture Epistemic and Aleatoric Uncertainty
PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure
Unofficial PyTorch Reimplementation of RandAugment.
A PyTorch implementation of Auxiliary Classifier GAN to generate CIFAR10 images.
Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"
[NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning
Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach
Weakly Supervised Learning of Instance Segmentation with Inter-pixel Relations, CVPR 2019 (Oral)
Datasets, Transforms and Models specific to Computer Vision