OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference

[BMVC 2023 (Oral)] SketchDreamer: Interactive Text-Augmented Creative Sketch Ideation

PyTorch library for solving imaging inverse problems using deep learning

A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc.).

Rectified Diffusion: Straightness Is Not Your Need

Official code repository of CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph

collection of diffusion model papers categorized by their subareas

[NeurIPS 2024] IMAGPose: A Unified Conditional Framework for Pose-Guided Person Generation. IMAGPose enables versatile pose-guided image generation with high detail fidelity, pose alignment, and cross-view consistency, overcoming limitations of existing methods.

Official PyTorch Implementation of: "MDMP: Multi-modal Diffusion for supervised Motion Predictions"

A curated list of recent diffusion models for video generation, editing, restoration, understanding, etc.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities. arXiv:2408.07666.

A Collection of AIGC Research Groups

[MMSP'24] Diffusion-based Bit-depth Expansion

A hands-on repository dedicated to building mainstream deep learning models from scratch using PyTorch

This project investigates the integration of alias-free resampling techniques, inspired by StyleGAN3, into the UNet architecture of Diffusion models. Our approach focuses on improving model performance without introducing new trainable parameters, maintaining efficiency and simplicity.

A paper list about large language models and multimodal models (Diffusion, VLM). From foundations to applications. It is only used to record papers for my personal needs.

A general fine-tuning kit geared toward diffusion models.

Crowd modeling with Denoising Diffusion Probabilisitic Models (DDPMs) for crowd macroproperties sequence samples.

Information and materials for the Turing's "robots-in-disguise" reading group on fundamental AI research.

SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models