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20172022
most citedLearning to Prune Filters in Convolutional Neural Networks

27 citations · 94 across the 15 of their papers we have counts for

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17 papers · 1 filter

cs.CV20223 cited

ALTO: Alternating Latent Topologies for Implicit 3D Reconstruction

Zhen Wang, Shijie Zhou, Jeong Joon Park +5

This work introduces alternating latent topologies (ALTO) for high-fidelity reconstruction of implicit 3D surfaces from noisy point clouds. Previous work identifies that the spatia…

cs.CV2022

Enhanced Low-resolution LiDAR-Camera Calibration Via Depth Interpolation and Supervised Contrastive Learning

Zhikang Zhang, Zifan Yu, Suya You +3

Motivated by the increasing application of low-resolution LiDAR recently, we target the problem of low-resolution LiDAR-camera calibration in this work. The main challenges are two…

cs.CV20222 cited

DefakeHop++: An Enhanced Lightweight Deepfake Detector

Hong-Shuo Chen, Shuowen Hu, Suya You +1

On the basis of DefakeHop, an enhanced lightweight Deepfake detector called DefakeHop++ is proposed in this work. The improvements lie in two areas. First, DefakeHop examines three…

cs.CV202111 cited

Geo-DefakeHop: High-Performance Geographic Fake Image Detection

Hong-Shuo Chen, Kaitai Zhang, Shuowen Hu +2

A robust fake satellite image detection method, called Geo-DefakeHop, is proposed in this work. Geo-DefakeHop is developed based on the parallel subspace learning (PSL) methodology…

cs.CV20211 cited

Meta-UDA: Unsupervised Domain Adaptive Thermal Object Detection using Meta-Learning

Vibashan VS, Domenick Poster, Suya You +2

Object detectors trained on large-scale RGB datasets are being extensively employed in real-world applications. However, these RGB-trained models suffer a performance drop under ad…

cs.CV20211 cited

UHP-SOT: An Unsupervised High-Performance Single Object Tracker

Zhiruo Zhou, Hongyu Fu, Suya You +2

An unsupervised online object tracking method that exploits both foreground and background correlations is proposed and named UHP-SOT (Unsupervised High-Performance Single Object T…