arXiv:2606. 06903v1 Announce Type: cross Abstract: Human image animation aims to generate a video from a static reference image, guided by pose information extracted from a driving video.
By Yuan Zeng, Yujia Shi, Yuhao Yang, Dongxia Liu, Zongqing Lu, Wenming Yang, Qingmin Liao
arXiv:2609.00505v1 Announce Type: new
Abstract: Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues...
By Sethuraman T V, Savya Khosla, Onkar Kishor Susladkar, Aditi Tiwari, Seoung Wug Oh, Kushal Kafle, Joon-Young Lee, Derek Hoiem, Simon Jenni
Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues like order, direction, and motion dynamics. Stand...
arXiv:2608.23410v1 Announce Type: new
Abstract: Photorealistic novel view synthesis of people remains challenging at high spatial resolutions and across multiple target cameras, where preserving iden...
By Federico Stella, Fei Jiang, Zhongshi Jiang, Zohar Barzelay, Emanuel Garbin, Amin Jourabloo, Liuhao Ge
arXiv:2606. 31981v1 Announce Type: cross Abstract: Creating photorealistic, animatable 3D human avatars from monocular images still largely depends on Linear Blend Skinning (LBS) and parametric body models, which constrain expressivity and often introduce artifacts due to imperfect fitting.
By Peng Li, Rawal Khirodkar, Junxuan Li, Yuan Dong, Chen Cao, Yuan Liu, Wenhan Luo, Yike Guo, Shunsuke Saito
Recent advances in generative models and technological innovations have significantly addressed the fundamental challenges of character image animation. However, existing approaches predominantly focus on character animation from a single reference image, substantially limiting their applicability in scenarios such as multiple character interaction animation.