HGC-Det applies hyperbolic geometry to constrain cross-modal distillation between images and point clouds, with added semantic-guided voxel optimization and feature aggregation, yielding improved accuracy-efficiency trade-offs on SUN RGB-D, ARKitScenes, KITTI, and nuScenes.
Shmamba: Structured hyperbolic state space model for audio-visual question answering
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AV-Master introduces dynamic adaptive focus sampling, modality preference modeling, and dual-path contrastive loss to outperform prior methods on audio-visual question answering benchmarks.
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Hyperbolic Distillation: Geometry-Guided Cross-Modal Transfer for Robust 3D Object Detection
HGC-Det applies hyperbolic geometry to constrain cross-modal distillation between images and point clouds, with added semantic-guided voxel optimization and feature aggregation, yielding improved accuracy-efficiency trade-offs on SUN RGB-D, ARKitScenes, KITTI, and nuScenes.
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AV-Master: Dual-Path Comprehensive Perception Makes Better Audio-Visual Question Answering
AV-Master introduces dynamic adaptive focus sampling, modality preference modeling, and dual-path contrastive loss to outperform prior methods on audio-visual question answering benchmarks.