25 citations · 59 across the 31 of their papers we have counts for
9 papers · 1 filter
GroundAnything: Reconciling Parallel Decoding with Precise Visual Grounding at Flash Speed
Qize Yu, Lianrui Fan, Bowen Ping +19
Autoregressive (AR) grounding models serialize spatial predictions, introducing sequential latency and imposing a causal order on output tokens. We view grounding as visual evidenc…
UniGarmentManip: A Unified Framework for Category-Level Garment Manipulation via Dense Visual Correspondence
Ruihai Wu, Haoran Lu, Yiyan Wang +2
Garment manipulation (e.g., unfolding, folding and hanging clothes) is essential for future robots to accomplish home-assistant tasks, while highly challenging due to the diversity…
Learning Part Motion of Articulated Objects Using Spatially Continuous Neural Implicit Representations
Yushi Du, Ruihai Wu, Yan Shen +1
Articulated objects (e.g., doors and drawers) exist everywhere in our life. Different from rigid objects, articulated objects have higher degrees of freedom and are rich in geometr…
Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly
Ruihai Wu, Chenrui Tie, Yushi Du +2
Shape assembly aims to reassemble parts (or fragments) into a complete object, which is a common task in our daily life. Different from the semantic part assembly (e.g., assembling…
Learning Foresightful Dense Visual Affordance for Deformable Object Manipulation
Ruihai Wu, Chuanruo Ning, Hao Dong
Understanding and manipulating deformable objects (e.g., ropes and fabrics) is an essential yet challenging task with broad applications. Difficulties come from complex states and…
DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Manipulation
Yan Zhao, Ruihai Wu, Zhehuan Chen +4
It is essential yet challenging for future home-assistant robots to understand and manipulate diverse 3D objects in daily human environments. Towards building scalable systems that…
AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions
Yian Wang, Ruihai Wu, Kaichun Mo +4
Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets, pose particular challenges for future home-assistant robots performing daily tasks in…
VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects
Ruihai Wu, Yan Zhao, Kaichun Mo +7
Perceiving and manipulating 3D articulated objects (e.g., cabinets, doors) in human environments is an important yet challenging task for future home-assistant robots. The space of…
Unpaired Image-to-Image Translation using Adversarial Consistency Loss
Yihao Zhao, Ruihai Wu, Hao Dong
Unpaired image-to-image translation is a class of vision problems whose goal is to find the mapping between different image domains using unpaired training data. Cycle-consistency…