4 papers
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…
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…
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…
4KAgent: Agentic Any Image to 4K Super-Resolution
Yushen Zuo, Qi Zheng, Mingyang Wu +10
We present 4KAgent, a unified agentic super-resolution generalist system designed to universally upscale any image to 4K resolution (and even higher, if applied iteratively). Our s…