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Robot learning in the era of foundation models: A survey
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Constructing a 3D scene capable of accommodating open-ended language queries, is a
pivotal pursuit in the domain of robotics, which facilitates robots in executing object …
pivotal pursuit in the domain of robotics, which facilitates robots in executing object …
MTMamba: Enhancing multi-task dense scene understanding by mamba-based decoders
Multi-task dense scene understanding, which learns a model for multiple dense prediction
tasks, has a wide range of application scenarios. Modeling long-range dependency and …
tasks, has a wide range of application scenarios. Modeling long-range dependency and …
Fmgs: Foundation model embedded 3d gaussian splatting for holistic 3d scene understanding
Precisely perceiving the geometric and semantic properties of real-world 3D objects is
crucial for the continued evolution of augmented reality and robotic applications. To this end …
crucial for the continued evolution of augmented reality and robotic applications. To this end …
Semantically-aware neural radiance fields for visual scene understanding: A comprehensive review
This review thoroughly examines the role of semantically-aware Neural Radiance Fields
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
(NeRFs) in visual scene understanding, covering an analysis of over 250 scholarly papers. It …
Nerf-mae: Masked autoencoders for self-supervised 3d representation learning for neural radiance fields
Neural fields excel in computer vision and robotics due to their ability to understand the 3D
visual world such as inferring semantics, geometry, and dynamics. Given the capabilities of …
visual world such as inferring semantics, geometry, and dynamics. Given the capabilities of …