most citedEV-Catcher: High-Speed Object Catching Using Low-latency Event-based Neural Networks

26 citations · 68 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2024

Track Everything Everywhere Fast and Robustly

Yunzhou Song, Jiahui Lei, Ziyun Wang +2

We propose a novel test-time optimization approach for efficiently and robustly tracking any pixel at any time in a video. The latest state-of-the-art optimization-based tracking t…

cs.RO2024

Scalable Networked Feature Selection with Randomized Algorithm for Robot Navigation

Vivek Pandey, Arash Amini, Guangyi Liu +4

We address the problem of sparse selection of visual features for localizing a team of robots navigating an unknown environment, where robots can exchange relative position measure…

cs.CV2023

ReFit: Recurrent Fitting Network for 3D Human Recovery

Yufu Wang, Kostas Daniilidis

We present Recurrent Fitting (ReFit), a neural network architecture for single-image, parametric 3D human reconstruction. ReFit learns a feedback-update loop that mirrors the strat…

cs.RO20235 cited

Learning to Navigate in Turbulent Flows with Aerial Robot Swarms: A Cooperative Deep Reinforcement Learning Approach

Diego Patiño, Siddharth Mayya, Juan Calderon +2

Aerial operation in turbulent environments is a challenging problem due to the chaotic behavior of the flow. This problem is made even more complex when a team of aerial robots is…

cs.CV20236 cited

Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance

Congyue Deng, Jiahui Lei, Bokui Shen +2

Equivariance has gained strong interest as a desirable network property that inherently ensures robust generalization. However, when dealing with complex systems such as articulate…

cs.CV20233 cited

NAP: Neural 3D Articulation Prior

Jiahui Lei, Congyue Deng, Bokui Shen +2

We propose Neural 3D Articulation Prior (NAP), the first 3D deep generative model to synthesize 3D articulated object models. Despite the extensive research on generating 3D object…