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SCEPTER is an open-source framework used for training, fine-tuning, and inference with generative models.
Image composition toolbox: everything you want to know about image composition or object insertion
PyTorch implementation of InstructDiffusion, a unifying and generic framework for aligning computer vision tasks with human instructions.
[CVPR 2024 Highlight] MIGC and [TPAMI 2024] MIGC++ (Official Implementation)
[TMLR] Official PyTorch implementation of "λ-ECLIPSE: Multi-Concept Personalized Text-to-Image Diffusion Models by Leveraging CLIP Latent Space"
[NeurIPS'23] "MagicBrush: A Manually Annotated Dataset for Instruction-Guided Image Editing".
Implementation of paper 'Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Models'
The first dataset of composite images with rationality score indicating whether the object placement in a composite image is reasonable.
[WACV'18] Where and Who? Automatic Semantic-Aware Person Composition
[ECCV 2022] Official code for "Learning Object Placement via Dual-path Graph Completion"
A discriminative object placement approach
An unofficial implementation of the paper "TopNet: Transformer-based Object Placement Network for Image Compositing", CVPR 2023.
A curated list of papers, code and resources pertaining to image composition/compositing or object insertion, which aims to generate realistic composite image.
[ICLR 2024] Official repo. for Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
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 th…
[CVPR 2023] OneFormer: One Transformer to Rule Universal Image Segmentation
Kandinsky 2 — multilingual text2image latent diffusion model
[NeurIPS2023] DatasetDM:Synthesizing Data with Perception Annotations Using Diffusion Models
🔥 [CVPR 2024] The official repo for Zero-Painter!
[NeurIPS 2024] RealCompo: Balancing Realism and Compositionality Improves Text-to-Image Diffusion Models
A collection of resources on controllable generation with text-to-image diffusion models.
stock predict with MLP,CNN,RNN,LSTM,Transformer and Transformer-LSTM