arXiv Computer Vision
KSG-Net: Key-Sparse and Global-Context Learning for Maritime 3D Ship Detection
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arXiv Machine Learning
Aug 19
Leveraging existing sparse point annotations for benthic imagery dense segmentation
The paper presents a method that leverages sparse expert point annotations from historical benthic surveys to improve dense segmentation of marine imagery. By using these points as visual prompts for the SAM2 foundation model and introducing a mechanism to filter out unreliable points, the authors generate high‑quality pseudo‑ground‑truth masks that train more accurate fine‑grained semantic segmentation models. The approach is validated on public benthic datasets and a new benchmark featuring real‑world sparse annotations, aiming to enable scalable ecological analysis.
arXiv AI
Jun 9
ATN3D: Density-Aware LiDAR-Radar Early 3D Object Detection Under Extreme Sparsity
arXiv:2606. 09634v1 Announce Type: cross Abstract: 3D object detection is the backbone of perception for automated vehicles (AV) and broader intelligent transportation systems applications.
arXiv Machine Learning
Jun 16
Analyzing Visual Aircraft Representations with Sparse Autoencoders
arXiv:2606. 15468v1 Announce Type: cross Abstract: Vision models can achieve strong performance on classification tasks, but the internal representations supporting their predictions are often difficult to interpret.
Hugging Face Trending Papers
Jun 8
ATN3D: Density-Aware LiDAR-Radar Early 3D Object Detection Under Extreme Sparsity
3D object detection is the backbone of perception for automated vehicles (AV) and broader intelligent transportation systems applications. Long-range detection is challenging because sensing evidence is sparse; yet this ``long-range'' scenario is routine in traffic.
arXiv Computer Vision
5d ago
Unleashing the Potential of Mamba: Boosting a LiDAR 3D Sparse Detector by Using Cross-Model Knowledge Distillation
arXiv:2409.11018v3 Announce Type: replace Abstract: The LiDAR 3D object detector that balances accuracy and speed is crucial for achieving real-time perception in autonomous driving. However, many ex...
Hugging Face Trending Papers
Aug 15
LightLoc++: Sensor-Robust Representation Learning for Efficient Outdoor LiDAR Localization
Scene coordinate regression (SCR) achieves strong performance in outdoor LiDAR localization, but it usually requires scene-specific training that can take days, limiting practical deployment. Recent w...