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20202026
most citedControlVideo: Training-free Controllable Text-to-Video Generation

34 citations · 56 across the 23 of their papers we have counts for

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5 papers · 1 filter

cs.CV2026

4DHumanDiff: Direct Text-to-4DGS Generation for Consistent 360-Degree Dynamic Humans

Renlong Wu, Haoran Chen, Yuxiang Wei +3

Generating high-quality 360-degree dynamic human assets from text prompts is challenging. Existing methods usually synthesize monocular or multi-view videos first and then fit a 4D…

cs.CV2026

Premier: Personalized Preference Modulation with Learnable User Embedding in Text-to-Image Generation

Zihao Wang, Yuxiang Wei, Xinpeng Zhou +5

Text-to-image generation has advanced rapidly, yet it still struggles to capture the nuanced user preferences. Existing approaches typically rely on multimodal large language model…

cs.CV2026

DreamLite: A Lightweight On-Device Unified Model for Image Generation and Editing

Kailai Feng, Yuxiang Wei, Bo Chen +5

Diffusion models have made significant progress in both text-to-image (T2I) generation and text-guided image editing. However, these models are typically built with billions of par…

cs.CV2026

CREval: An Automated Interpretable Evaluation for Creative Image Manipulation under Complex Instructions

Chonghuinan Wang, Zihan Chen, Yuxiang Wei +5

Instruction-based multimodal image manipulation has recently made rapid progress. However, existing evaluation methods lack a systematic and human-aligned framework for assessing m…

cs.HC2026

CoEditor++: Instruction-based Visual Editing via Cognitive Reasoning

Minheng Ni, Yutao Fan, Zhengyuan Yang +6

Recent advances in large multimodal models (LMMs) have enabled instruction-based image editing, allowing users to modify visual content via natural language descriptions. However,…