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20242026
most citedTowards Small Object Editing: A Benchmark Dataset and A Training-Free Approach

288 citations · 289 across the 4 of their papers we have counts for

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cs.CV2026

Mass Concept Erasure in Diffusion Models with Concept Hierarchy

Jiahang Tu, Ye Li, Yiming Wu +3

The success of diffusion models has raised concerns about the generation of unsafe or harmful content, prompting concept erasure approaches that fine-tune modules to suppress speci…

cs.CV2025

Towards Consumer-Grade Cybersickness Prediction: Multi-Model Alignment for Real-Time Vision-Only Inference

Yitong Zhu, Zhuowen Liang, Yiming Wu +2

Cybersickness remains a major obstacle to the widespread adoption of immersive virtual reality (VR), particularly in consumer-grade environments. While prior methods rely on invasi…

cs.CV2024

MoTe: Learning Motion-Text Diffusion Model for Multiple Generation Tasks

Yiming Wu, Wei Ji, Kecheng Zheng +2

Recently, human motion analysis has experienced great improvement due to inspiring generative models such as the denoising diffusion model and large language model. While the exist…

cs.CV2024288 cited

Towards Small Object Editing: A Benchmark Dataset and A Training-Free Approach

Qihe Pan, Zhen Zhao, Zicheng Wang +5

A plethora of text-guided image editing methods has recently been developed by leveraging the impressive capabilities of large-scale diffusion-based generative models especially St…

cs.CV2024

Individual Content and Motion Dynamics Preserved Pruning for Video Diffusion Models

Yiming Wu, Zhenghao Chen, Huan Wang +1

The high computational cost and slow inference time are major obstacles to deploying Video Diffusion Models (VDMs). To overcome this, we introduce a new Video Diffusion Model Compr…