activity
20242026
collaborators

13 papers

cs.CV2026

Focusing on What Matters: Saliency-Harnessing Accurate Routing for Diffusion MoE

Haoyou Deng, Keyu Yan, Chaojie Mao +4

Mixture-of-Experts (MoE) architectures have emerged as a powerful paradigm for scaling diffusion models in visual generation. Recent advancements have focused on adaptively allocat…

cs.CV2026

DenseGRPO: From Sparse to Dense Reward for Flow Matching Model Alignment

Haoyou Deng, Keyu Yan, Chaojie Mao +4

Recent GRPO-based approaches built on flow matching models have shown remarkable improvements in human preference alignment for text-to-image generation. Nevertheless, they still s…

cs.CV2025

Unison: A Fully Automatic, Task-Universal, and Low-Cost Framework for Unified Understanding and Generation

Shihao Zhao, Yitong Chen, Zeyinzi Jiang +5

Unified understanding and generation is a highly appealing research direction in multimodal learning. There exist two approaches: one trains a transformer via an auto-regressive pa…

cs.CV2025

Lego-Edit: A General Image Editing Framework with Model-Level Bricks and MLLM Builder

Qifei Jia, Yu Liu, Yajie Chai +6

Instruction-based image editing has garnered significant attention due to its direct interaction with users. However, real-world user instructions are immensely diverse, and existi…

cs.CV2025

AdPO: Enhancing the Adversarial Robustness of Large Vision-Language Models with Preference Optimization

Chaohu Liu, Tianyi Gui, Yu Liu +1

Large Vision-Language Models (LVLMs), such as GPT-4o and LLaVA, have recently witnessed remarkable advancements and are increasingly being deployed in real-world applications. Howe…

cs.CL2025

Penrose Tiled Low-Rank Compression and Section-Wise Q&A Fine-Tuning: A General Framework for Domain-Specific Large Language Model Adaptation

Chuan-Wei Kuo, Siyu Chen, Chenqi Yan +1

Large language models (LLMs) hold great promise for specialized scientific domains such as materials science, yet adapting them efficiently and accurately to domain-specific knowle…

cs.CV2025

Rethinking Video Tokenization: A Conditioned Diffusion-based Approach

Nianzu Yang, Pandeng Li, Liming Zhao +8

Existing video tokenizers typically use the traditional Variational Autoencoder (VAE) architecture for video compression and reconstruction. However, to achieve good performance, i…

cs.CV2025

VACE: All-in-One Video Creation and Editing

Zeyinzi Jiang, Zhen Han, Chaojie Mao +3

Diffusion Transformer has demonstrated powerful capability and scalability in generating high-quality images and videos. Further pursuing the unification of generation and editing…

cs.CV2025

ICE-Bench: A Unified and Comprehensive Benchmark for Image Creating and Editing

Yulin Pan, Xiangteng He, Chaojie Mao +4

Image generation has witnessed significant advancements in the past few years. However, evaluating the performance of image generation models remains a formidable challenge. In thi…

cs.CV2025

ACE++: Instruction-Based Image Creation and Editing via Context-Aware Content Filling

Chaojie Mao, Jingfeng Zhang, Yulin Pan +4

We report ACE++, an instruction-based diffusion framework that tackles various image generation and editing tasks. Inspired by the input format for the inpainting task proposed by…

cs.CV2025

INFELM: In-depth Fairness Evaluation of Large Text-To-Image Models

Di Jin, Xing Liu, Yu Liu +7

The rapid development of large language models (LLMs) and large vision models (LVMs) have propelled the evolution of multi-modal AI systems, which have demonstrated the remarkable…

cs.CV2024

ACE: All-round Creator and Editor Following Instructions via Diffusion Transformer

Zhen Han, Zeyinzi Jiang, Yulin Pan +5

Diffusion models have emerged as a powerful generative technology and have been found to be applicable in various scenarios. Most existing foundational diffusion models are primari…

cs.CV2024

ControlEdit: A MultiModal Local Clothing Image Editing Method

Di Cheng, YingJie Shi, ShiXin Sun +3

Multimodal clothing image editing refers to the precise adjustment and modification of clothing images using data such as textual descriptions and visual images as control conditio…