83 citations · 252 across the 13 of their papers we have counts for
13 papers
Neural Program Synthesis with Query
Di Huang, Rui Zhang, Xing Hu +6
Aiming to find a program satisfying the user intent given input-output examples, program synthesis has attracted increasing interest in the area of machine learning. Despite the pr…
Distilling Object Detectors with Feature Richness
Zhixing Du, Rui Zhang, Ming Chang +4
In recent years, large-scale deep models have achieved great success, but the huge computational complexity and massive storage requirements make it a great challenge to deploy the…
Eden: A Unified Environment Framework for Booming Reinforcement Learning Algorithms
Ruizhi Chen, Xiaoyu Wu, Yansong Pan +12
With AlphaGo defeats top human players, reinforcement learning(RL) algorithms have gradually become the code-base of building stronger artificial intelligence(AI). The RL algorithm…
Hindsight Value Function for Variance Reduction in Stochastic Dynamic Environment
Jiaming Guo, Rui Zhang, Xishan Zhang +6
Policy gradient methods are appealing in deep reinforcement learning but suffer from high variance of gradient estimate. To reduce the variance, the state value function is applied…
Domain-Specific Suppression for Adaptive Object Detection
Yu Wang, Rui Zhang, Shuo Zhang +4
Domain adaptation methods face performance degradation in object detection, as the complexity of tasks require more about the transferability of the model. We propose a new perspec…
DWM: A Decomposable Winograd Method for Convolution Acceleration
Di Huang, Xishan Zhang, Rui Zhang +9
Winograd's minimal filtering algorithm has been widely used in Convolutional Neural Networks (CNNs) to reduce the number of multiplications for faster processing. However, it is on…
Asymmetric GAN for Unpaired Image-to-image Translation
Yu Li, Sheng Tang, Rui Zhang +3
Unpaired image-to-image translation problem aims to model the mapping from one domain to another with unpaired training data. Current works like the well-acknowledged Cycle GAN pro…
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers
Xishan Zhang, Shaoli Liu, Rui Zhang +8
Adaptive Precision Training: Quantify Back Propagation in Neural Networks with Fixed-point Numbers. Recent emerged quantization technique has been applied to inference of deep neur…
Consensus Feature Network for Scene Parsing
Tianyi Wu, Sheng Tang, Rui Zhang +2
Scene parsing is challenging as it aims to assign one of the semantic categories to each pixel in scene images. Thus, pixel-level features are desired for scene parsing. However, c…
Harmonic Unpaired Image-to-image Translation
Rui Zhang, Tomas Pfister, Jia Li
The recent direction of unpaired image-to-image translation is on one hand very exciting as it alleviates the big burden in obtaining label-intensive pixel-to-pixel supervision, bu…
Tree-structured Kronecker Convolutional Network for Semantic Segmentation
Tianyi Wu, Sheng Tang, Rui Zhang +2
Most existing semantic segmentation methods employ atrous convolution to enlarge the receptive field of filters, but neglect partial information. To tackle this issue, we firstly p…
Style Separation and Synthesis via Generative Adversarial Networks
Rui Zhang, Sheng Tang, Yu Li +4
Style synthesis attracts great interests recently, while few works focus on its dual problem "style separation". In this paper, we propose the Style Separation and Synthesis Genera…
CGNet: A Light-weight Context Guided Network for Semantic Segmentation
Tianyi Wu, Sheng Tang, Rui Zhang +1
The demand of applying semantic segmentation model on mobile devices has been increasing rapidly. Current state-of-the-art networks have enormous amount of parameters hence unsuita…