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20212026
most citedPartAfford: Part-level Affordance Discovery from 3D Objects

13 citations · 17 across the 19 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.RO2024

Ag2Manip: Learning Novel Manipulation Skills with Agent-Agnostic Visual and Action Representations

Puhao Li, Tengyu Liu, Yuyang Li +6

Autonomous robotic systems capable of learning novel manipulation tasks are poised to transform industries from manufacturing to service automation. However, modern methods (e.g.,…

cs.CV2024★ 1 cited

PhyRecon: Physically Plausible Neural Scene Reconstruction

Junfeng Ni, Yixin Chen, Bohan Jing +7

We address the issue of physical implausibility in multi-view neural reconstruction. While implicit representations have gained popularity in multi-view 3D reconstruction, previous…

cs.CV2024

Move as You Say, Interact as You Can: Language-guided Human Motion Generation with Scene Affordance

Zan Wang, Yixin Chen, Baoxiong Jia +7

Despite significant advancements in text-to-motion synthesis, generating language-guided human motion within 3D environments poses substantial challenges. These challenges stem pri…

cs.CV2024

AnySkill: Learning Open-Vocabulary Physical Skill for Interactive Agents

Jieming Cui, Tengyu Liu, Nian Liu +3

Traditional approaches in physics-based motion generation, centered around imitation learning and reward shaping, often struggle to adapt to new scenarios. To tackle this limitatio…

cs.CV2024

Scaling Up Dynamic Human-Scene Interaction Modeling

Nan Jiang, Zhiyuan Zhang, Hongjie Li +6

Confronting the challenges of data scarcity and advanced motion synthesis in human-scene interaction modeling, we introduce the TRUMANS dataset alongside a novel HSI motion synthes…