PhD candidate @CVMI-Lab | Previous Senior Computer Vision Engineer in IDEA-CVR @IDEA-Research
visualization. a collection of visualization function
447pytorch-distributed-training. Simple tutorials on Pytorch DDP training
280TRAR-VQA. [ICCV 2021] Official implementation of the paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering"
68pytorch-pooling. Test different pooling method used in CNN for Computer Vision Task
35Learn-Detectron2-From-Scratch. Detectron2 Learning Notes Sharing
10knowledge-graph-visualization. knowledge graph system based on Neo4j and Vue
9ViT.pytorch. The Pytorch reimplementation of Vision Transformer
9config-builder. a list of config-builder repo and tutorials which may help you to build your own config file
7vision-mlp-oneflow. Vision MLP Models Based on OneFlow
7x-classification. a framework for image classification based on pytorch
6mini-classification. lightweight and efficient classification project based on pytorch-lightning
4pytorch-models. Computer vision models on Pytorch
4TRAR-Feature-Extraction. Grid features extraction for ICCV 2021 paper "TRAR: Routing the Attention Spans in Transformers for Visual Question Answering"
3rentainhe.github.io. Personal homepage
3vision-mlp. A collection of SOTA vision mlp models based on Pytorch
3simple-imagenet-test. A simple test code on Imagenet
2knowledge-graph-backend. the backend of knowledge graph system based on Springboot
2MaskDINO. [CVPR 2023] Official implementation of the paper "Mask DINO: Towards A Unified Transformer-based Framework for Object Detection and Segmentation"
1ViT-pytorch. Pytorch reimplementation of the Vision Transformer (An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale)
1T2T-ViT. ICCV2021, Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
1MambaOut. MambaOut: Do We Really Need Mamba for Vision?
1sam2. The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.
1ConvNeXt. Code release for ConvNeXt model
1Awesome-Anything. General AI methods for Anything: AnyObject, AnyGeneration, AnyModel, AnyTask, AnyX
1rexnet. Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models
1transformers. 🤗 Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
1what_I_have_read. Just for self-motivation
1ollama. Get up and running with Llama 3.1, Mistral, Gemma 2, and other large language models.
1deep-learning-knowledge. A collection of cv-interview problems and answers
1paper-reading.
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