arXiv Computer Vision
Learned Suppression for 3D Keypoint Detection with a Graph-Transformer Backbone
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Jun 3
Learned Non-Maximum Suppression for 3D Object Detection
arXiv:2606. 03568v1 Announce Type: cross Abstract: Post-processing is a critical stage in LiDAR-based 3D object detection, where dense and overlapping proposals must be filtered for compact and reliable perception.
arXiv AI
Aug 21
Open-Vocabulary 3D Object Detection with Co-Distillation Discovery and Dual Guidance Robust Training
arXiv:2608. 19973v1 Announce Type: cross Abstract: Recently, open-vocabulary 3D object detection (3D-OVD) has gained increasing attention for its ability to detect unseen objects in 3D scenes.
arXiv Computer Vision
Aug 25
GeoMix: Descriptor-Free Visual Localization via Global Context and Multi-Detector Training
arXiv:2607.02486v2 Announce Type: replace Abstract: Descriptor-free visual localization eliminates high-dimensional descriptor storage, preserves scene privacy, and simplifies map maintenance, yet it...
arXiv AI
Jun 18
A Survey on Deep Learning Architectures for Point Cloud Classification and Segmentation
arXiv:2605. 17131v2 Announce Type: replace-cross Abstract: Point cloud stands as the most widely adopted format for representing 3D shapes and scenes due to its simplicity and geometric fidelity.
arXiv Computer Vision
Sep 1
AQ3D: Adaptive Query Transformer for 3D Instance Segmentation
arXiv:2608.30618v1 Announce Type: new Abstract: Transformer-based decoders for 3D instance segmentation typically commit to a fixed number of queries and positional modeling calibrated on the trainin...
arXiv AI
Jul 1
Mitigating Positional Leakage in 3D Masked Autoencoders for Robust Representation Learning
arXiv:2606. 31570v1 Announce Type: cross Abstract: Masked autoencoding has emerged as a prominent paradigm for self-supervised learning on 3D point clouds, achieving competitive performance across downstream tasks.