2 citations · 4 across the 9 of their papers we have counts for
6 papers · 1 filter
TCP-SSM: Efficient Vision State Space Models with Token-Conditioned Poles
Sara Shoouri, Morteza Tavakoli Taba, Hun-Seok Kim
State Space Models (SSMs) have emerged as a compelling alternative to attention models for long-range vision tasks, offering input-dependent recurrence with linear complexity. Howe…
HyperLiDAR: Adaptive Post-Deployment LiDAR Segmentation via Hyperdimensional Computing
Ivannia Gomez Moreno, Yi Yao, Ye Tian +7
LiDAR semantic segmentation plays a pivotal role in 3D scene understanding for edge applications such as autonomous driving. However, significant challenges remain for real-world d…
Adaptive LiDAR Scanning: Harnessing Temporal Cues for Efficient 3D Object Detection via Multi-Modal Fusion
Sara Shoouri, Morteza Tavakoli Taba, Hun-Seok Kim
Multi-sensor fusion using LiDAR and RGB cameras significantly enhances 3D object detection task. However, conventional LiDAR sensors perform dense, stateless scans, ignoring the st…
SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation
Mingyu Yang, Jitong Lu, Hun-Seok Kim
Multi-modal 3D semantic segmentation is vital for applications such as autonomous driving and virtual reality (VR). To effectively deploy these models in real-world scenarios, it i…
Efficient Computation Sharing for Multi-Task Visual Scene Understanding
Sara Shoouri, Mingyu Yang, Zichen Fan +1
Solving multiple visual tasks using individual models can be resource-intensive, while multi-task learning can conserve resources by sharing knowledge across different tasks. Despi…
Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality Selection
Mingyu Yang, Yu Chen, Hun-Seok Kim
In recent years, deep learning-based approaches for visual-inertial odometry (VIO) have shown remarkable performance outperforming traditional geometric methods. Yet, all existing…