activity
20182022
most citedDeep Discriminative Clustering Analysis

43 citations · 62 across the 6 of their papers we have counts for

collaborators

11 papers

cs.CV20221 cited

Gradient Concealment: Free Lunch for Defending Adversarial Attacks

Sen Pei, Jiaxi Sun, Xiaopeng Zhang +1

Recent studies show that the deep neural networks (DNNs) have achieved great success in various tasks. However, even the \emph{state-of-the-art} deep learning based classifiers are…

cs.CV2021

Differentiable Convolution Search for Point Cloud Processing

Xing Nie, Yongcheng Liu, Shaohong Chen +6

Exploiting convolutional neural networks for point cloud processing is quite challenging, due to the inherent irregular distribution and discrete shape representation of point clou…

cs.CV2020

Dynamic Scale Training for Object Detection

Yukang Chen, Peizhen Zhang, Zeming Li +5

We propose a Dynamic Scale Training paradigm (abbreviated as DST) to mitigate scale variation challenge in object detection. Previous strategies like image pyramid, multi-scale tra…

cs.CV20195 cited

FontGAN: A Unified Generative Framework for Chinese Character Stylization and De-stylization

Xiyan Liu, Gaofeng Meng, Shiming Xiang +1

Chinese character synthesis involves two related aspects, i.e., style maintenance and content consistency. Although some methods have achieved remarkable success in synthesizing a…

cs.CV2019

DensePoint: Learning Densely Contextual Representation for Efficient Point Cloud Processing

Yongcheng Liu, Bin Fan, Gaofeng Meng +3

Point cloud processing is very challenging, as the diverse shapes formed by irregular points are often indistinguishable. A thorough grasp of the elusive shape requires sufficientl…

cs.CV20192 cited

Joint haze image synthesis and dehazing with mmd-vae losses

Zongliang Li, Chi Zhang, Gaofeng Meng +1

Fog and haze are weathers with low visibility which are adversarial to the driving safety of intelligent vehicles equipped with optical sensors like cameras and LiDARs. Therefore i…