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Swift Parameter-free Attention Network for Efficient Super-Resolution

AI Image SIgnal Processing and Computational Photography - Bokeh Rendering , Reversed ISP Challenge, Model-Based Image Signal Processors via Learnable Dictionaries. Official repo for NTIRE and AIM …

This is our implementation of a trainable bilateral filter layer (PyTorch)

ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型

PyTorch implementation of Guided Image Filtering

Open-sourced codes for MiniGPT-4 and MiniGPT-v2 (https://minigpt-4.github.io, https://minigpt-v2.github.io/)

Macaw-LLM: Multi-Modal Language Modeling with Image, Video, Audio, and Text Integration

Convolutional PyTorch debayering / demosaicing layers

An ultimately comprehensive paper list of Vision Transformer/Attention, including papers, codes, and related websites

A Collection of Papers and Codes in CVPR2023/2022 about low level vision

[CVPR2023] FastInst: A Simple Query-Based Model for Real-Time Instance Segmentation

Handheld Multi-image Super-resolution [Wronski et al., SIGGRAPH19]. Non-official GPU-supported Python implementation.

Official repo for consistency models.

SOTA for Burst Super-resolution, Low-light Burst Image Enhancement, Burst Image De-noising

Official repository of the Fried Rice Lab, including code resources of the following our works: ESWT [arXiv], etc. This repository also implements many useful features and out-of-the-box image rest…

🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

[TPAMI 2024] Official repo of "ETPNav: Evolving Topological Planning for Vision-Language Navigation in Continuous Environments"

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

This is an offical implementation of the CVPR2022's paper [Learning the Degradation Distribution for Blind Image Super-Resolution](https://arxiv.org/abs/2203.04962)