most citedTimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

1 citations · 1 across the 10 of their papers we have counts for

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10 papers

cs.CV2026

PRISM: Prompt Refinement via Image-grounded Self-rewarding Mechanism for Text-to-Image Generation

Guo Tang, HongJie Luo, Tianxu Wang +2

Text-to-image generation models can synthesize high-quality images from natural language descriptions, but their performance remains highly sensitive to prompt formulation. Existin…

cs.CV2026

PortraitGen: Exemplar-Driven GRPO with Dual-Reward Guidance for Photorealistic Portrait Generation

Xiaomin Li, Qian Liang, Yinan Li +5

Reinforcement Learning like Group Relative Policy Optimization (GRPO) has significantly advanced text-to-image post-training. However, current methods often favor superficial aesth…

cs.CV2026

WeGenBench: A Multidimensional Diagnostic Benchmark towards Text-to-Image Model Optimization

Qian Liang, Xiaomin Li, Ying Zhang +6

Recent text-to-image generation models have demonstrated remarkable capabilities in synthesizing highly realistic images from text inputs alone. Although existing benchmarks can ev…

cs.CV2026

ClueAegis: Heuristic-to-Reasoning Cognitive-skill Learning for Unified Evidence-based Synthetic Image Detection

Huangsen Cao, Hongkang Chu, Yuxi Li +6

The rapid advancement of generative models has made synthetic images increasingly realistic, challenging reliable detection. Existing methods are often limited to end-to-end classi…

cs.CV2025

REVEAL: Reasoning-Enhanced Forensic Evidence Analysis for Explainable AI-Generated Image Detection

Huangsen Cao, Qin Mei, Zhiheng Li +9

The rapid progress of visual generative models has made AI-generated images increasingly difficult to distinguish from authentic ones, posing growing risks to social trust and info…

cs.CV2025

WeTok: Powerful Discrete Tokenization for High-Fidelity Visual Reconstruction

Shaobin Zhuang, Yiwei Guo, Canmiao Fu +7

Visual tokenizer is a critical component for vision generation. However, the existing tokenizers often face unsatisfactory trade-off between compression ratios and reconstruction f…

cs.CV2025

Video-GPT via Next Clip Diffusion

Shaobin Zhuang, Zhipeng Huang, Ying Zhang +6

GPT has shown its remarkable success in natural language processing. However, the language sequence is not sufficient to describe spatial-temporal details in the visual world. Alte…

cs.CV2025★ 1 cited

TimeStep Master: Asymmetrical Mixture of Timestep LoRA Experts for Versatile and Efficient Diffusion Models in Vision

Shaobin Zhuang, Yiwei Guo, Yanbo Ding +7

Diffusion models have driven the advancement of vision generation over the past years. However, it is often difficult to apply these large models in downstream tasks, due to massiv…

cs.CV2025

WeGen: A Unified Model for Interactive Multimodal Generation as We Chat

Zhipeng Huang, Shaobin Zhuang, Canmiao Fu +7

Existing multimodal generative models fall short as qualified design copilots, as they often struggle to generate imaginative outputs once instructions are less detailed or lack th…

cs.CV2025

Get In Video: Add Anything You Want to the Video

Shaobin Zhuang, Zhipeng Huang, Binxin Yang +7

Video editing increasingly demands the ability to incorporate specific real-world instances into existing footage, yet current approaches fundamentally fail to capture the unique v…