activity
20212026
most citedStreaming Radiance Fields for 3D Video Synthesis

26 citations · 42 across the 13 of their papers we have counts for

collaborators
Showing 2026Show all

6 papers · 1 filter

cs.CV2026

RASA: Disentangled Spatial-Motional Priors for Cross-Identity Character Animation

Zhen Xiao, Zhen Shen, Zhaofan Qiu +3

Cross-identity character animation aims to drive a target identity from a reference image to follow the motion of a source character from a driving video. The core challenge lies i…

cs.RO2026

LD4WAM: Learning Latent Dynamics from Human Videos for World Action Models

Zhenhao Shen, Jiaqi Liang, Jasper Lu +11

Human video is playing an increasingly central role in training World Action Models (WAMs), owing to its diversity and low collection cost relative to teleoperated robot data. Howe…

cs.CV2026

DSA: Dynamic Step Allocation for Fast Autoregressive Video Generation

Thanh-Tung Le, Yunhan Zhao, Menglei Chai +5

Video diffusion transformers have achieved state-of-the-art visual quality, but their high inference cost remains a major bottleneck for real-time applications. Recent distillation…

cs.RO2026

RoboWM-Bench: A Benchmark for Evaluating World Models in Robotic Manipulation

Feng Jiang, Yang Chen, Kyle Xu +8

Recent advances in large-scale video world models have enabled increasingly realistic future prediction, raising the prospect of using generated videos as scalable supervision for…

cs.CV2026

HiDream-O1-Image: A Natively Unified Image Generative Foundation Model with Pixel-level Unified Transformer

Qi Cai, Jingwen Chen, Chengmin Gao +22

The evolution of visual generative models has long been constrained by fragmented architectures relying on disjoint text encoders and external VAEs. In this report, we present HiDr…

cs.RO2026

From Seeing to Simulating: Generative High-Fidelity Simulation with Digital Cousins for Generalizable Robot Learning and Evaluation

Jasper Lu, Zhenhao Shen, Yuanfei Wang +8

Learning robust robot policies in real-world environments requires diverse data augmentation, yet scaling real-world data collection is costly due to the need for acquiring physica…