Stars
This repository contains the official implementation of the research papers, "MobileCLIP" CVPR 2024 and "MobileCLIP2" TMLR August 2025
Pytorch Implementation (unofficial) of the paper "Mean Flows for One-step Generative Modeling" by Geng et al.
A clean PyTorch implementation of SiamFC tracking/training, evaluated on 7 datasets.
Official pytorch reimplementation for "Semantic Line Detection and Its Applications"
PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.
使用pytorch_quantization对yolov8进行量化
Code for NeurIPS 2024 paper - The GAN is dead; long live the GAN! A Modern Baseline GAN - by Huang et al.
The demo of YOLOv8-based object detection & instance segmentation & human pose
Original reference implementation of "3D Gaussian Splatting for Real-Time Radiance Field Rendering"
This is the official testing code of the baseline method presented at the CVPR 2023 NTIRE Real-Time 4K Super-Resolution Challenge. We provide model and pre-trained checkpoints.
PyTorch implementation of MAR+DiffLoss https://arxiv.org/abs/2406.11838
LPIPS metric. pip install lpips
Pytorch implementation of Diffusion Models (https://arxiv.org/pdf/2006.11239.pdf)
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
This repository is an official implementation of the paper "LW-DETR: A Transformer Replacement to YOLO for Real-Time Detection".
[CVPR 2024] Real-Time Open-Vocabulary Object Detection
Official Repo For OMG-LLaVA and OMG-Seg codebase [CVPR-24 and NeurIPS-24]
[CVPR 2024] Official RT-DETR (RTDETR paddle pytorch), Real-Time DEtection TRansformer, DETRs Beat YOLOs on Real-time Object Detection. 🔥 🔥 🔥
This repository provides the code and model checkpoints for AIMv1 and AIMv2 research projects.
Code for "Learning to summarize from human feedback"
A large-scale, fine-grained, diverse preference dataset (and models).
arXiv LaTeX Cleaner: Easily clean the LaTeX code of your paper to submit to arXiv
[CVPR2023] This is an official implementation of paper "DETRs with Hybrid Matching".