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20232026
most citedDreaMoving: A Human Video Generation Framework based on Diffusion Models

1 citations · 2 across the 8 of their papers we have counts for

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cs.CV2026★ 1 cited

A Mechanistic View on Video Generation as World Models: State and Dynamics

Luozhou Wang, Zhifei Chen, Yihua Du +11

Large-scale video generation models have demonstrated emergent physical coherence, positioning them as potential world models. However, a gap remains between contemporary "stateles…

cs.CV2025

AnimateAnywhere: Rouse the Background in Human Image Animation

Xiaoyu Liu, Mingshuai Yao, Yabo Zhang +5

Human image animation aims to generate human videos of given characters and backgrounds that adhere to the desired pose sequence. However, existing methods focus more on human acti…

cs.CV2025

DiffuEraser: A Diffusion Model for Video Inpainting

Xiaowen Li, Haolan Xue, Peiran Ren +1

Recent video inpainting algorithms integrate flow-based pixel propagation with transformer-based generation to leverage optical flow for restoring textures and objects using inform…

cs.CV2024

Multi-modal Learnable Queries for Image Aesthetics Assessment

Zhiwei Xiong, Yunfan Zhang, Zhiqi Shen +2

Image aesthetics assessment (IAA) is attracting wide interest with the prevalence of social media. The problem is challenging due to its subjective and ambiguous nature. Instead of…

cs.CV2024

SmartControl: Enhancing ControlNet for Handling Rough Visual Conditions

Xiaoyu Liu, Yuxiang Wei, Ming Liu +4

Human visual imagination usually begins with analogies or rough sketches. For example, given an image with a girl playing guitar before a building, one may analogously imagine how…

cs.CV2024

VideoElevator: Elevating Video Generation Quality with Versatile Text-to-Image Diffusion Models

Yabo Zhang, Yuxiang Wei, Xianhui Lin +5

Text-to-image diffusion models (T2I) have demonstrated unprecedented capabilities in creating realistic and aesthetic images. On the contrary, text-to-video diffusion models (T2V)…