79 citations · 160 across the 13 of their papers we have counts for
11 papers · 1 filter
Deeply-Conditioned Image Compression via Self-Generated Priors
Zhineng Zhao, Zhihai He, Zikun Zhou +2
Learned image compression (LIC) has shown great promise for achieving high rate-distortion performance. However, current LIC methods are often limited in their capability to model…
Structure-Preserving Progressive Low-rank Image Completion for Defending Adversarial Attacks
Zhiqun Zhao, Hengyou Wang, Hao Sun +1
Deep neural networks recognize objects by analyzing local image details and summarizing their information along the inference layers to derive the final decision. Because of this,…
Unsupervised Deep Metric Learning with Transformed Attention Consistency and Contrastive Clustering Loss
Yang Li, Shichao Kan, Zhihai He
Existing approaches for unsupervised metric learning focus on exploring self-supervision information within the input image itself. We observe that, when analyzing images, human ey…
Ensemble Generative Cleaning with Feedback Loops for Defending Adversarial Attacks
Jianhe Yuan, Zhihai He
Effective defense of deep neural networks against adversarial attacks remains a challenging problem, especially under powerful white-box attacks. In this paper, we develop a new me…
Reciprocal Learning Networks for Human Trajectory Prediction
Hao Sun, Zhiqun Zhao, Zhihai He
We observe that the human trajectory is not only forward predictable, but also backward predictable. Both forward and backward trajectories follow the same social norms and obey th…
Snowball: Iterative Model Evolution and Confident Sample Discovery for Semi-Supervised Learning on Very Small Labeled Datasets
Yang Li, Jianhe Yuan, Zhiqun Zhao +2
In this work, we develop a joint sample discovery and iterative model evolution method for semi-supervised learning on very small labeled training sets. We propose a master-teacher…
Progressive Neural Networks for Image Classification
Zhi Zhang, Guanghan Ning, Yigang Cen +4
The inference structures and computational complexity of existing deep neural networks, once trained, are fixed and remain the same for all test images. However, in practice, it is…
Dual Path Networks for Multi-Person Human Pose Estimation
Guanghan Ning, Zhihai He
The task of multi-person human pose estimation in natural scenes is quite challenging. Existing methods include both top-down and bottom-up approaches. The main advantage of bottom…
Knowledge Projection for Deep Neural Networks
Zhi Zhang, Guanghan Ning, Zhihai He
While deeper and wider neural networks are actively pushing the performance limits of various computer vision and machine learning tasks, they often require large sets of labeled d…
Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object Tracking
Guanghan Ning, Zhi Zhang, Chen Huang +3
In this paper, we develop a new approach of spatially supervised recurrent convolutional neural networks for visual object tracking. Our recurrent convolutional network exploits th…
A Classification Leveraged Object Detector
Miao Sun, Tony X. Han, Zhihai He
Currently, the state-of-the-art image classification algorithms outperform the best available object detector by a big margin in terms of average precision. We, therefore, propose…