28 citations · 126 across the 18 of their papers we have counts for
18 papers
VAG: Dual-Stream Video-Action Generation for Embodied Data Synthesis
Xiaolei Lang, Yang Wang, Yukun Zhou +10
Recent advances in robot foundation models trained on large-scale human teleoperation data have enabled robots to perform increasingly complex real-world tasks. However, scaling th…
DriveDreamer-Policy: A Geometry-Grounded World-Action Model for Unified Generation and Planning
Yang Zhou, Xiaofeng Wang, Hao Shao +8
Recently, world-action models (WAM) have emerged to bridge vision-language-action (VLA) models and world models, unifying their reasoning and instruction-following capabilities and…
GigaWorld-0: World Models as Data Engine to Empower Embodied AI
GigaWorld Team, Angen Ye, Boyuan Wang +22
World models are emerging as a foundational paradigm for scalable, data-efficient embodied AI. In this work, we present GigaWorld-0, a unified world model framework designed explic…
GigaBrain-0: A World Model-Powered Vision-Language-Action Model
GigaBrain Team, Angen Ye, Boyuan Wang +24
Training Vision-Language-Action (VLA) models for generalist robots typically requires large-scale real-world robot data, which is expensive and time-consuming to collect. The ineff…
DriveGen3D: Boosting Feed-Forward Driving Scene Generation with Efficient Video Diffusion
Weijie Wang, Jiagang Zhu, Zeyu Zhang +14
We present DriveGen3D, a novel framework for generating high-quality and highly controllable dynamic 3D driving scenes that addresses critical limitations in existing methodologies…
RoboTransfer: Controllable Geometry-Consistent Video Diffusion for Manipulation Policy Transfer
Liu Liu, Xiaofeng Wang, Guosheng Zhao +7
The goal of general-purpose robotics is to create agents that can seamlessly adapt to and operate in diverse, unstructured human environments. Imitation learning has become a key p…
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchma…
Masked Face Recognition Challenge: The WebFace260M Track Report
Zheng Zhu, Guan Huang, Jiankang Deng +9
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training da…
Semi-Global Shape-aware Network
Pengju Zhang, Yihong Wu, Jiagang Zhu
Non-local operations are usually used to capture long-range dependencies via aggregating global context to each position recently. However, most of the methods cannot preserve obje…
Cluster Regularized Quantization for Deep Networks Compression
Yiming Hu, Jianquan Li, Xianlei Long +4
Deep neural networks (DNNs) have achieved great success in a wide range of computer vision areas, but the applications to mobile devices is limited due to their high storage and co…
Multi-loss-aware Channel Pruning of Deep Networks
Yiming Hu, Siyang Sun, Jianquan Li +3
Channel pruning, which seeks to reduce the model size by removing redundant channels, is a popular solution for deep networks compression. Existing channel pruning methods usually…
Action Machine: Rethinking Action Recognition in Trimmed Videos
Jiagang Zhu, Wei Zou, Liang Xu +6
Existing methods in video action recognition mostly do not distinguish human body from the environment and easily overfit the scenes and objects. In this work, we present a concept…
An Efficient Optical Flow Based Motion Detection Method for Non-stationary Scenes
Junjie Huang, Wei Zou, Zheng Zhu +1
Real-time motion detection in non-stationary scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. These challeng…
Optical Flow Based Online Moving Foreground Analysis
Junjie Huang, Wei Zou, Zheng Zhu +1
Obtained by moving object detection, the foreground mask result is unshaped and can not be directly used in most subsequent processes. In this paper, we focus on this problem and a…
Optical Flow Based Real-time Moving Object Detection in Unconstrained Scenes
Junjie Huang, Wei Zou, Jiagang Zhu +1
Real-time moving object detection in unconstrained scenes is a difficult task due to dynamic background, changing foreground appearance and limited computational resource. In this…
End-to-end Video-level Representation Learning for Action Recognition
Jiagang Zhu, Wei Zou, Zheng Zhu
From the frame/clip-level feature learning to the video-level representation building, deep learning methods in action recognition have developed rapidly in recent years. However,…
Learning Gating ConvNet for Two-Stream based Methods in Action Recognition
Jiagang Zhu, Wei Zou, Zheng Zhu
For the two-stream style methods in action recognition, fusing the two streams' predictions is always by the weighted averaging scheme. This fusion method with fixed weights lacks…