[NeurIPS 2024 Oral][GPT beats diffusion🔥] [scaling laws in visual generation📈] Official impl. of "Visual Autoregressive Modeling: Scalable Image Generation via Next-Scale Prediction". An *ultra-sim…

Code for ECCV 2022 paper "DICE: Leveraging Sparsification for Out-of-Distribution Detection"

PyTorch implementation of CIDER (How to exploit hyperspherical embeddings for out-of-distribution detection), ICLR 2023

The Pytorch implemetation of "FeatWalk: Enhancing Few-Shot Classification through Local View Leveraging", AAAI 2024.

source code for ICML'24 paper "When and how does in-distribution label help out-of-distribution detection?"

🎮 A beautiful little Sudoku game built with Svelte and TailwindCSS.

PyTorch code and models for the DINOv2 self-supervised learning method.

PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO

[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

A blog for understanding graph neural network

Adaptation of vision-language models (CLIP) to downstream tasks using local and global prompts.

Out-of-distribution detection, robustness, and generalization resources. The repository contains a curated list of papers, tutorials, books, videos, articles and open-source libraries etc

[ICCV2023] "Vision HGNN: An Image is More than a Graph of Nodes" by Yan Han, Peihao Wang, Souvik Kundu, Ying Ding, and Zhangyang Wang

PyTorch implementation of Masked Autoencoder

Unofficial PyTorch implementation of Masked Autoencoders Are Scalable Vision Learners

PyTorch implementation of MAE https//arxiv.org/abs/2111.06377

Unofficial implementation of RealFill

Prompt Learning for Vision-Language Models (IJCV'22, CVPR'22)

CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image

High-Resolution Image Synthesis with Latent Diffusion Models

Code for ACMMM2024 paper: FodFoM: Fake Outlier Data by Foundation Models Creates Stronger Visual Out-of-Distribution Detector

Flowcon: Out-of-Distribution Detection using Flow-Based Contrastive Learning [In Progress]

[NeurIPS2023] LoCoOp: Few-Shot Out-of-Distribution Detection via Prompt Learning

The official implementation of CVPR 24' Paper "Learning Transferable Negative Prompts for Out-of-Distribution Detection"

A collection of LLM papers, blogs, and projects, with a focus on OpenAI o1 🍓 and reasoning techniques.

Pytorch分布式训练框架

Code for AAAI2024 paper: TagFog：Textual Anchor Guidance and Fake Outlier Generation for Visual Out-of-distribution Detection