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20232026
most citedTF-ICON: Diffusion-Based Training-Free Cross-Domain Image Composition

2 citations · 3 across the 15 of their papers we have counts for

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12 papers · 1 filter

cs.CV2026

MFSR: MeanFlow Distillation for One Step Real-World Image Super Resolution

Ruiqing Wang, Kai Zhang, Yuanzhi Zhu +3

Diffusion- and flow-based models have advanced Real-world Image Super-Resolution (Real-ISR), but their multi-step sampling makes inference slow and hard to deploy. One-step distill…

cs.CV2026

LUVE : Latent-Cascaded Ultra-High-Resolution Video Generation with Dual Frequency Experts

Chen Zhao, Jiawei Chen, Hongyu Li +6

Recent advances in video diffusion models have significantly improved visual quality, yet ultra-high-resolution (UHR) video generation remains a formidable challenge due to the com…

cs.CV2025

DragFlow: Unleashing DiT Priors with Region Based Supervision for Drag Editing

Zihan Zhou, Shilin Lu, Shuli Leng +4

Drag-based image editing has long suffered from distortions in the target region, largely because the priors of earlier base models, Stable Diffusion, are insufficient to project o…

cs.CV2025

Does FLUX Already Know How to Perform Physically Plausible Image Composition?

Shilin Lu, Zhuming Lian, Zihan Zhou +3

Image composition aims to seamlessly insert a user-specified object into a new scene, but existing models struggle with complex lighting (e.g., accurate shadows, water reflections)…

cs.CV2025

Visual Document Understanding and Reasoning: A Multi-Agent Collaboration Framework with Agent-Wise Adaptive Test-Time Scaling

Xinlei Yu, Chengming Xu, Zhangquan Chen +6

The dominant paradigm of monolithic scaling in Vision-Language Models (VLMs) is failing for understanding and reasoning in documents, yielding diminishing returns as it struggles w…

cs.CV2025

Set You Straight: Auto-Steering Denoising Trajectories to Sidestep Unwanted Concepts

Leyang Li, Shilin Lu, Yan Ren +1

Ensuring the ethical deployment of text-to-image models requires effective techniques to prevent the generation of harmful or inappropriate content. While concept erasure methods o…