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cs.GR2026
FFAvatar: Few-Shot, Feed-Forward, and Generalizable Avatar Reconstruction
Thuan Hoang Nguyen, Jiahao Luo, Yinyu Nie +3
Avatar reconstruction has traditionally relied on per-subject optimization that requires hours of computation or on expensive preprocessing that limits scalability. We introduce FF…
cs.CV2026
ScaleMoGen: Autoregressive Next-Scale Prediction for Human Motion Generation
Inwoo Hwang, Hojun Jang, Bing Zhou +3
We present ScaleMoGen, a scale-wise autoregressive framework for text-driven human motion generation. Unlike conventional autoregressive approaches that rely on standard next-token…
cs.CV2026
Semantic One-Dimensional Tokenizer for Image Reconstruction and Generation
Yunpeng Qu, Kaidong Zhang, Yukang Ding +2
Visual generative models based on latent space have achieved great success, underscoring the significance of visual tokenization. Mapping images to latents boosts efficiency and en…