activity
20192022
most citedA Spacecraft Dataset for Detection, Segmentation and Parts Recognition

6 citations · 13 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

8 papers · 1 filter

cs.CV2022

Update Compression for Deep Neural Networks on the Edge

Bo Chen, Ali Bakhshi, Gustavo Batista +2

An increasing number of artificial intelligence (AI) applications involve the execution of deep neural networks (DNNs) on edge devices. Many practical reasons motivate the need to…

cs.CV20221 cited

Asynchronous Optimisation for Event-based Visual Odometry

Daqi Liu, Alvaro Parra, Yasir Latif +3

Event cameras open up new possibilities for robotic perception due to their low latency and high dynamic range. On the other hand, developing effective event-based vision algorithm…

cs.CV20211 cited

Occlusion-Robust Object Pose Estimation with Holistic Representation

Bo Chen, Tat-Jun Chin, Marius Klimavicius

Practical object pose estimation demands robustness against occlusions to the target object. State-of-the-art (SOTA) object pose estimators take a two-stage approach, where the fir…

cs.CV20215 cited

Physical Adversarial Attacks on an Aerial Imagery Object Detector

Andrew Du, Bo Chen, Tat-Jun Chin +4

Deep neural networks (DNNs) have become essential for processing the vast amounts of aerial imagery collected using earth-observing satellite platforms. However, DNNs are vulnerabl…

cs.CV20216 cited

A Spacecraft Dataset for Detection, Segmentation and Parts Recognition

Dung Anh Hoang, Bo Chen, Tat-Jun Chin

Virtually all aspects of modern life depend on space technology. Thanks to the great advancement of computer vision in general and deep learning-based techniques in particular, ove…

cs.CV2020

Topological Sweep for Multi-Target Detection of Geostationary Space Objects

Daqi Liu, Bo Chen, Tat-Jun Chin +1

Conducting surveillance of the Earth's orbit is a key task towards achieving space situational awareness (SSA). Our work focuses on the optical detection of man-made objects (e.g.,…