1 citations · 1 across the 20 of their papers we have counts for
27 papers
RADIANT: Object-Centric Feed-Forward Global Illumination
Sarah Zhang, Zhiyang Dou, Minghao Guo +2
Feed-forward neural renderers synthesize global illumination across novel 3D scenes without per-scene optimization or runtime ray tracing. Existing transformer-based renderers toke…
T-WLA: Bridging Slow Vision and Fast Touch
Kaichen Zhou, Yuzhen Chen, Hannah Yao +14
In contact-rich manipulation, contact conditions can change before a visual policy updates its action plan. Recomputing the plan through the visual policy adds latency, while tacti…
An Unexpected Robot Policy: Early Evaluations of GPT-6 Astra on RoboDojo and Beyond
Wenbo Zhang, Kaixuan Wang, Yutao Ouyang +9
Embodied AI systems are often organized into System 1 and System 2. System 1 is typically a pretrained policy that generates actions at high frequency, whereas System 2 is often in…
S4R: Scaling for Rigid-Body Interpenetration Resolution
Zhiyang Dou, Ang Zhao, Chen Peng +8
Rigid-body interpenetration frequently occurs in procedurally assembled and generated scenes and must be removed before downstream applications such as physical simulation. We pres…
SPOT: Spatial Perception-Oriented Long-Horizon Humanoid Teleoperation
Lixing Fang, Ziyan Xiong, Sunli Chen +2
High-quality demonstration data is becoming a central bottleneck for training general-purpose humanoid robots. While recent humanoid teleoperation systems have made substantial pro…
Better Call CineCrew: Consistent Ultra-Long Narrative-to-Film Generation
Jiaben Chen, Sixun Dong, Qinhong Zhou +4
Long-form narrative-to-film generation requires shot-level controllability and cross-clip consistency in both visual identity and character behavior-requirements that remain diffic…
UniMate: One Unified Model to Animate Diverse Skeletons
Linzhan Mou, Jiahui Lei, Zhiyang Dou +4
Recent advances in automatic rigging now deliver animation-ready 3D assets at scale, yet generating the motion to drive them remains a bottleneck. Existing learned animators are to…
HarnessEval-W: Agentifying the Evaluation of Visual Worlds
Weiliang Chen, Haowen Sun, Jun Gao +40
A benchmark should deliver more than a scalar score: what makes an evaluation trustworthy is the reasoning that justifies the score. This is especially critical for world models, w…
RoboEdit: Turning Human Manipulation Videos into Scalable Robot Experience
Yaowei Guo, Zeng Tao, Yuxin Jiang +7
Collecting robot hand-object interaction data is costly and embodiment-specific, yet abundant human-object videos remain unusable for robot training. We present RoboEdit, a human-t…
GeoBridge: Decoupled Semantic Conditioning for Generative Image Geolocalization
Zhiyang Dou, Xumeng Han, Fengde Peng +4
Multimodal large language models (MLLMs) have advanced image geolocalization mainly by improving how they reason about geographic cues. How that reasoning isdecoded into coordinate…
Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning
Shilin Shan, Chuhao Zhou, Ruize Wang +30
Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capability is particularly critical…
NeuralActuator: Neural Actuation Modeling for Robot Dynamics and External Force Perception
Zhiyang Dou, John U. Onyemelukwe, Hangxing Zhang +9
Differentiable simulators have advanced policy learning and model-based control across robotic tasks. Yet actuator dynamics remain underexplored and can be a major source of sim-to…
HumanScale: Egocentric Human Video Can Outperform Real-Robot Data for Embodied Pretraining
Juncheng Ma, Jianxin Bi, Yufan Deng +19
Embodied foundation models are expected to benefit from data scaling like large language models, but face a much tighter data bottleneck. Teleoperated real-robot trajectories remai…
RigidFormer: Learning Rigid Dynamics using Transformers
Zhiyang Dou, Minghao Guo, Haixu Wu +3
Learning-based simulation of multi-object rigid-body dynamics remains difficult because contact is discontinuous and errors compound over long horizons. Most existing methods remai…
Soft Anisotropic Diagrams for Differentiable Image Representation
Laki Iinbor, Zhiyang Dou, Wojciech Matusik
We introduce Soft Anisotropic Diagrams (SAD), an explicit and differentiable image representation parameterized by a set of adaptive sites in the image plane. In SAD, each site spe…
TS-Attn: Temporal-wise Separable Attention for Multi-Event Video Generation
Hongyu Zhang, Yufan Deng, Zilin Pan +6
Generating high-quality videos from complex temporal descriptions that contain multiple sequential actions is a key unsolved problem. Existing methods are constrained by an inheren…
Switch-JustDance: Benchmarking Whole Body Motion Tracking Controllers Using a Commercial Console Game
Jeonghwan Kim, Wontaek Kim, Yidan Lu +9
Recent advances in whole-body robot control have enabled humanoid and legged robots to perform increasingly agile and coordinated motions. However, standardized benchmarks for eval…
Go to Zero: Towards Zero-shot Motion Generation with Million-scale Data
Ke Fan, Shunlin Lu, Minyue Dai +6
Generating diverse and natural human motion sequences based on textual descriptions constitutes a fundamental and challenging research area within the domains of computer vision, g…
SymBridge: A Human-in-the-Loop Cyber-Physical Interactive System for Adaptive Human-Robot Symbiosis
Haoran Chen, Yiteng Xu, Yiming Ren +14
The development of intelligent robots seeks to seamlessly integrate them into the human world, providing assistance and companionship in daily life and work, with the ultimate goal…
ScaMo: Exploring the Scaling Law in Autoregressive Motion Generation Model
Shunlin Lu, Jingbo Wang, Zeyu Lu +6
The scaling law has been validated in various domains, such as natural language processing (NLP) and massive computer vision tasks; however, its application to motion generation re…
Towards Interactive Global Geolocation Assistant
Zhiyang Dou, Zipeng Wang, Xumeng Han +3
Global geolocation, which seeks to predict the geographical location of images captured anywhere in the world, is one of the most challenging tasks in the field of computer vision.…
ViMoE: An Empirical Study of Designing Vision Mixture-of-Experts
Xumeng Han, Longhui Wei, Zhiyang Dou +6
Mixture-of-Experts (MoE) models embody the divide-and-conquer concept and are a promising approach for increasing model capacity, demonstrating excellent scalability across multipl…
Dynamic Realms: 4D Content Analysis, Recovery and Generation with Geometric, Topological and Physical Priors
Zhiyang Dou
My research focuses on the analysis, recovery, and generation of 4D content, where 4D includes three spatial dimensions (x, y, z) and a temporal dimension t, such as shape and moti…
AutoPSV: Automated Process-Supervised Verifier
Jianqiao Lu, Zhiyang Dou, Hongru Wang +4
In this work, we propose a novel method named \textbf{Auto}mated \textbf{P}rocess-\textbf{S}upervised \textbf{V}erifier (\textbf{\textsc{AutoPSV}}) to enhance the reasoning capabil…