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Found 5 papers, 4 papers with code
MMScan: A Multi-Modal 3D Scene Dataset with Hierarchical Grounded Language Annotations
With the emergence of LLMs and their integration with other data modalities, multi-modal 3D perception attracts more attention due to its connectivity to the physical world and makes rapid progress.
EmbodiedScan: A Holistic Multi-Modal 3D Perception Suite Towards Embodied AI
In the realm of computer vision and robotics, embodied agents are expected to explore their environment and carry out human instructions.
Beyond Object Recognition: A New Benchmark towards Object Concept Learning
To support OCL, we build a densely annotated knowledge base including extensive labels for three levels of object concept (category, attribute, affordance), and the causal relations of three levels.
Learning Single/Multi-Attribute of Object with Symmetry and Group
To model the compositional nature of these concepts, it is a good choice to learn them as transformations, e. g., coupling and decoupling.
Symmetry and Group in Attribute-Object Compositions
To model the compositional nature of these general concepts, it is a good choice to learn them through transformations, such as coupling and decoupling.
Ranked #1 on
Compositional Zero-Shot Learning
on MIT-States
(Top-1 accuracy % metric)
