Low-rank decoder adaptation enables efficient test-time optimization for zero-shot depth completion by updating only the subspace containing depth-relevant information.
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Ilov3Splat learns view-consistent CLIP and instance feature fields on 3D Gaussians to support open-vocabulary object selection and segmentation without category labels.
SWoMo decouples symbolic rule-based motion modeling via scene graphs from visual realism via diffusion models, trained through inverse pairing of real cataract surgery videos reconstructed in the simulator for sim-to-real translation.
citing papers explorer
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Efficient Test-Time Optimization for Depth Completion via Low-Rank Decoder Adaptation
Low-rank decoder adaptation enables efficient test-time optimization for zero-shot depth completion by updating only the subspace containing depth-relevant information.
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Ilov3Splat: Instance-Level Open-Vocabulary 3D Scene Understanding in Gaussian Splatting
Ilov3Splat learns view-consistent CLIP and instance feature fields on 3D Gaussians to support open-vocabulary object selection and segmentation without category labels.
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SWoMo: Neuro-Symbolic World Model for Cataract Surgery Simulation
SWoMo decouples symbolic rule-based motion modeling via scene graphs from visual realism via diffusion models, trained through inverse pairing of real cataract surgery videos reconstructed in the simulator for sim-to-real translation.