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Zelin Ye

7 accepted papers

2025

Demonstrating ViSafe: Vision-enabled Safety for High-speed Detect and Avoid

RSS 2025poster

Maintaining visual separation is crucial to achieving safe and seamless high-density operation of airborne vehicles in shared airspace, where pilots currently shoulder this responsibility. To automate this, we present ViSafe, a high-speed airborne vision-only collision avoidance system. Designed un…

Cited by 0PDFScholar
2023

CRIN: Rotation-Invariant Point Cloud Analysis and Rotation Estimation via Centrifugal Reference Frame

AAAI 2023technical

Various recent methods attempt to implement rotation-invariant 3D deep learning by replacing the input coordinates of points with relative distances and angles. Due to the incompleteness of these low-level features, they have to undertake the expense of losing global information. In this paper, we p…

2022

Canonical Voting: Towards Robust Oriented Bounding Box Detection in 3D Scenes

CVPR 2022poster

3D object detection has attracted much attention thanks to the advances in sensors and deep learning methods for point clouds. Current state-of-the-art methods like VoteNet regress direct offset towards object centers and box orientations with an additional Multi-Layer-Perceptron network. Both their…

Cited by 15PDFcodeScholar
2022

Multimodal Object Detection via Probabilistic Ensembling

ECCV 2022poster

"Object detection with multimodal inputs can improve many safety-critical systems such as autonomous vehicles (AVs). Motivated by AVs that operate in both day and night, we study multimodal object detection with RGB and thermal cameras, since the latter provides much stronger object signatures under…

2020

Transferable Active Grasping and Real Embodied Dataset

ICRA 2020poster

Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects. We adopt a reinforcement learning (RL) framework and 3D vision architectures to search for feasible viewpoints for grasping by the use of hand-mounted RGB-D ca…

Cited by 26SourcecodeScholar
2019

TendencyRL: Multi-stage Discriminative Hints for Efficient Goal-Oriented Reverse Curriculum Learning

IROS 2019poster

Deep reinforcement learning algorithms have been proven successful in a variety of simulation tasks with dense reward feedback. However, real-world RL applications, e.g. robotic manipulation, remain challenging as most of them are multi-stage and a positive reward can only be received when the final…

Cited by 4SourceScholar