137 citations · 180 across the 5 of their papers we have counts for
8 papers
Semi-Supervised Single-View 3D Reconstruction via Prototype Shape Priors
Zhen Xing, Hengduo Li, Zuxuan Wu +1
The performance of existing single-view 3D reconstruction methods heavily relies on large-scale 3D annotations. However, such annotations are tedious and expensive to collect. Semi…
2D or not 2D? Adaptive 3D Convolution Selection for Efficient Video Recognition
Hengduo Li, Zuxuan Wu, Abhinav Shrivastava +1
3D convolutional networks are prevalent for video recognition. While achieving excellent recognition performance on standard benchmarks, they operate on a sequence of frames with 3…
Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers
Chen Zhu, Renkun Ni, Ping-yeh Chiang +3
Convex relaxations are effective for training and certifying neural networks against norm-bounded adversarial attacks, but they leave a large gap between certifiable and empirical…
Learning from Noisy Anchors for One-stage Object Detection
Hengduo Li, Zuxuan Wu, Chen Zhu +3
State-of-the-art object detectors rely on regressing and classifying an extensive list of possible anchors, which are divided into positive and negative samples based on their inte…
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
Chen Zhu, W. Ronny Huang, Ali Shafahi +4
Clean-label poisoning attacks inject innocuous looking (and "correctly" labeled) poison images into training data, causing a model to misclassify a targeted image after being train…
An Analysis of Pre-Training on Object Detection
Hengduo Li, Bharat Singh, Mahyar Najibi +2
We provide a detailed analysis of convolutional neural networks which are pre-trained on the task of object detection. To this end, we train detectors on large datasets like OpenIm…