51 citations · 63 across the 13 of their papers we have counts for
15 papers
T-Rex: Tactile-Reactive Dexterous Manipulation
Dantong Niu, Zhuoyang Liu, Zekai Wang +31
The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based Vision-Language-Action (VLA) mo…
Playful Agentic Robot Learning
Junyi Zhang, Jiaxin Ge, Hanjun Yoo +17
Current agentic robot systems can write executable Code-as-Policy programs, observe feedback, and revise behavior across multiple attempts, but they remain largely task-driven: reu…
Cambrian-P: Pose-Grounded Video Understanding
Jihan Yang, Zifan Zhao, Xichen Pan +6
Camera pose matters. The position and orientation of each viewpoint define a shared spatial coordinate frame that relates observations across video frames. Yet this signal is large…
LoGeR: Long-Context Geometric Reconstruction with Hybrid Memory
Junyi Zhang, Charles Herrmann, Junhwa Hur +5
Feedforward geometric foundation models achieve strong short-window reconstruction, yet scaling them to minutes-long videos is bottlenecked by quadratic attention complexity or lim…
Selfi: Self Improving Reconstruction Engine via 3D Geometric Feature Alignment
Youming Deng, Songyou Peng, Junyi Zhang +5
Novel View Synthesis (NVS) has traditionally relied on models with explicit 3D inductive biases combined with known camera parameters from Structure-from-Motion (SfM) beforehand. R…
Visual Imitation Enables Contextual Humanoid Control
Arthur Allshire, Hongsuk Choi, Junyi Zhang +7
How can we teach humanoids to climb staircases and sit on chairs using the surrounding environment context? Arguably, the simplest way is to just show them-casually capture a human…
St4RTrack: Simultaneous 4D Reconstruction and Tracking in the World
Haiwen Feng, Junyi Zhang, Qianqian Wang +5
Dynamic 3D reconstruction and point tracking in videos are typically treated as separate tasks, despite their deep connection. We propose St4RTrack, a feed-forward framework that s…
Pre-training Auto-regressive Robotic Models with 4D Representations
Dantong Niu, Yuvan Sharma, Haoru Xue +5
Foundation models pre-trained on massive unlabeled datasets have revolutionized natural language and computer vision, exhibiting remarkable generalization capabilities, thus highli…
DenseMatcher: Learning 3D Semantic Correspondence for Category-Level Manipulation from a Single Demo
Junzhe Zhu, Yuanchen Ju, Junyi Zhang +4
Dense 3D correspondence can enhance robotic manipulation by enabling the generalization of spatial, functional, and dynamic information from one object to an unseen counterpart. Co…
MonST3R: A Simple Approach for Estimating Geometry in the Presence of Motion
Junyi Zhang, Charles Herrmann, Junhwa Hur +5
Estimating geometry from dynamic scenes, where objects move and deform over time, remains a core challenge in computer vision. Current approaches often rely on multi-stage pipeline…
Telling Left from Right: Identifying Geometry-Aware Semantic Correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur +4
While pre-trained large-scale vision models have shown significant promise for semantic correspondence, their features often struggle to grasp the geometry and orientation of insta…
A Tale of Two Features: Stable Diffusion Complements DINO for Zero-Shot Semantic Correspondence
Junyi Zhang, Charles Herrmann, Junhwa Hur +4
Text-to-image diffusion models have made significant advances in generating and editing high-quality images. As a result, numerous approaches have explored the ability of diffusion…
From Isolated Islands to Pangea: Unifying Semantic Space for Human Action Understanding
Yong-Lu Li, Xiaoqian Wu, Xinpeng Liu +8
Action understanding has attracted long-term attention. It can be formed as the mapping from the physical space to the semantic space. Typically, researchers built datasets accordi…
LayoutDiffusion: Improving Graphic Layout Generation by Discrete Diffusion Probabilistic Models
Junyi Zhang, Jiaqi Guo, Shizhao Sun +2
Creating graphic layouts is a fundamental step in graphic designs. In this work, we present a novel generative model named LayoutDiffusion for automatic layout generation. As layou…
Mining Cross-Person Cues for Body-Part Interactiveness Learning in HOI Detection
Xiaoqian Wu, Yong-Lu Li, Xinpeng Liu +3
Human-Object Interaction (HOI) detection plays a crucial role in activity understanding. Though significant progress has been made, interactiveness learning remains a challenging p…