26 citations · 42 across the 6 of their papers we have counts for
6 papers
Speed by Simplicity: A Single-Stream Architecture for Fast Audio-Video Generative Foundation Model
SII-GAIR, Sand. ai, : +43
We present daVinci-MagiHuman, an open-source audio-video generative foundation model for human-centric generation. daVinci-MagiHuman jointly generates synchronized video and audio…
MAGI-1: Autoregressive Video Generation at Scale
Sand. ai, Hansi Teng, Hongyu Jia +36
We present MAGI-1, a world model that generates videos by autoregressively predicting a sequence of video chunks, defined as fixed-length segments of consecutive frames. Trained to…
Compact Real-time Radiance Fields with Neural Codebook
Lingzhi Li, Zhongshu Wang, Zhen Shen +2
Reconstructing neural radiance fields with explicit volumetric representations, demonstrated by Plenoxels, has shown remarkable advantages on training and rendering efficiency, whi…
4K-NeRF: High Fidelity Neural Radiance Fields at Ultra High Resolutions
Zhongshu Wang, Lingzhi Li, Zhen Shen +2
In this paper, we present a novel and effective framework, named 4K-NeRF, to pursue high fidelity view synthesis on the challenging scenarios of ultra high resolutions, building on…
Compressing Volumetric Radiance Fields to 1 MB
Lingzhi Li, Zhen Shen, Zhongshu Wang +2
Approximating radiance fields with volumetric grids is one of promising directions for improving NeRF, represented by methods like Plenoxels and DVGO, which achieve super-fast trai…
Streaming Radiance Fields for 3D Video Synthesis
Lingzhi Li, Zhen Shen, Zhongshu Wang +2
We present an explicit-grid based method for efficiently reconstructing streaming radiance fields for novel view synthesis of real world dynamic scenes. Instead of training a singl…