CAMixerSR: Only Details Need More “Attention” (CVPR 2024)

Code for Learning Subject-Aware Cropping by Outpainting Professional Photos

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

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.

Let us control diffusion models!

PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation

PaddlePaddle Implementation of "Rethinking Image Cropping: Exploring Diverse Compositions from Global Views"

A dataset that includes photos downloaded from Flickr and annotations that indicates a local window representing a good composition.

Official implementation for ECCV2022 paper: Human-centric Image Cropping with Partition-aware and Content-preserving Features.

CLIP+MLP Aesthetic Score Predictor

[ICCV 2023, Official Code] for paper "Thinking Image Color Aesthetics Assessment: Models, Datasets and Benchmarks". Official Weights and Demos provided. 首个面向图像色彩主观美学评估的数据集、算法和benchmark.

LayoutDM: Discrete Diffusion Model for Controllable Layout Generation [Inoue+, CVPR2023]

implementation of “MaskPLAN: Masked Generative Layout Planning from Partial Input”

[CVPR24 Oral] Official repository for RALF: Retrieval-Augmented Layout Transformer for Content-Aware Layout Generation

[WACV 2024] Training-Free Layout Control with Cross-Attention Guidance

Diffusion model papers, survey, and taxonomy

(N=1,2,3)-dimensional unfold (im2col) and fold (col2im) in PyTorch

🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.

PyTorch implementation of SwAV https//arxiv.org/abs/2006.09882

Official Implementation for PlugIn Inversion

biastuning for SAM on medical datasets

Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"

Masked Autoencoder Guided Segmentation at Pixel Resolution

Segment Anything in Medical Images

Grounded Language-Image Pre-training