5 papers
DSAQuant: Denoising-Stage-Aligned Quantization-Aware Training for Video Generation
Shuaiting Li, Zelin Gao, Haibin Shen +3
Video diffusion models (VDMs) have achieved impressive progress in text-to-video generation, but their high memory and computational costs hinder practical deployment. Quantization…
Infinite Worlds with Versatile Interactions
Zelin Gao, Qiuyu Wang, Jiapeng Zhu +17
We present LingBot-World 2.0 (also known as LingBot-World-Infinity), an advanced iteration of LingBot-World featuring four distinct upgrades. (1) Our model achieves an unbounded in…
Causal World Modeling for Robot Control
Lin Li, Qihang Zhang, Yiming Luo +9
This work highlights that video world modeling, alongside vision-language pre-training, establishes a fresh and independent foundation for robot learning. Intuitively, video world…
The More You See in 2D, the More You Perceive in 3D
Xinyang Han, Zelin Gao, Angjoo Kanazawa +2
Humans can infer 3D structure from 2D images of an object based on past experience and improve their 3D understanding as they see more images. Inspired by this behavior, we introdu…
HG3-NeRF: Hierarchical Geometric, Semantic, and Photometric Guided Neural Radiance Fields for Sparse View Inputs
Zelin Gao, Weichen Dai, Yu Zhang
Neural Radiance Fields (NeRF) have garnered considerable attention as a paradigm for novel view synthesis by learning scene representations from discrete observations. Nevertheless…