4 papers · 1 filter
Class Geometry as Supervision for Sample-Efficient Open-World Detection
Akash Rao, Zhou Chen, Revanth Reddy Palem +3
Open-world object detection requires models to recognize known categories, reject unfamiliar objects, and incorporate new classes over time. This is especially challenging in scarc…
Generalized Event Partonomy Inference with Structured Hierarchical Predictive Learning
Zhou Chen, Joe Lin, Sathyanarayanan N. Aakur\\
Humans naturally perceive continuous experience as a hierarchy of temporally nested events, fine-grained actions embedded within coarser routines. Replicating this structure in com…
CRAFT: A Neuro-Symbolic Framework for Visual Functional Affordance Grounding
Zhou Chen, Joe Lin, Sathyanarayanan N. Aakur
We introduce CRAFT, a neuro-symbolic framework for interpretable affordance grounding, which identifies the objects in a scene that enable a given action (e.g., "cut"). CRAFT integ…
Self-supervised Learning of Rotation-invariant 3D Point Set Features using Transformer and its Self-distillation
Takahiko Furuya, Zhoujie Chen, Ryutarou Ohbuchi +1
Invariance against rotations of 3D objects is an important property in analyzing 3D point set data. Conventional 3D point set DNNs having rotation invariance typically obtain accur…