44 citations · 89 across the 15 of their papers we have counts for
17 papers
Isolation and Impartial Aggregation: A Paradigm of Incremental Learning without Interference
Yabin Wang, Zhiheng Ma, Zhiwu Huang +3
This paper focuses on the prevalent performance imbalance in the stages of incremental learning. To avoid obvious stage learning bottlenecks, we propose a brand-new stage-isolation…
Multi-agent Actor-Critic with Time Dynamical Opponent Model
Yuan Tian, Klaus-Rudolf Kladny, Qin Wang +2
In multi-agent reinforcement learning, multiple agents learn simultaneously while interacting with a common environment and each other. Since the agents adapt their policies during…
Neural Architecture Search for Efficient Uncalibrated Deep Photometric Stereo
Francesco Sarno, Suryansh Kumar, Berk Kaya +3
We present an automated machine learning approach for uncalibrated photometric stereo (PS). Our work aims at discovering lightweight and computationally efficient PS neural network…
Direct Differentiable Augmentation Search
Aoming Liu, Zehao Huang, Zhiwu Huang +1
Data augmentation has been an indispensable tool to improve the performance of deep neural networks, however the augmentation can hardly transfer among different tasks and datasets…
Efficient Conditional GAN Transfer with Knowledge Propagation across Classes
Mohamad Shahbazi, Zhiwu Huang, Danda Pani Paudel +2
Generative adversarial networks (GANs) have shown impressive results in both unconditional and conditional image generation. In recent literature, it is shown that pre-trained GANs…
Spectral Tensor Train Parameterization of Deep Learning Layers
Anton Obukhov, Maxim Rakhuba, Alexander Liniger +4
We study low-rank parameterizations of weight matrices with embedded spectral properties in the Deep Learning context. The low-rank property leads to parameter efficiency and permi…
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution
Yan Wu, Zhiwu Huang, Suryansh Kumar +3
Modern solutions to the single image super-resolution (SISR) problem using deep neural networks aim not only at better performance accuracy but also at a lighter and computationall…
Facial Emotion Recognition with Noisy Multi-task Annotations
Siwei Zhang, Zhiwu Huang, Danda Pani Paudel +1
Human emotions can be inferred from facial expressions. However, the annotations of facial expressions are often highly noisy in common emotion coding models, including categorical…
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
Dario Fuoli, Zhiwu Huang, Shuhang Gu +23
This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR)…
Off-Policy Reinforcement Learning for Efficient and Effective GAN Architecture Search
Yuan Tian, Qin Wang, Zhiwu Huang +5
In this paper, we introduce a new reinforcement learning (RL) based neural architecture search (NAS) methodology for effective and efficient generative adversarial network (GAN) ar…
Neural Architecture Search as Sparse Supernet
Yan Wu, Aoming Liu, Zhiwu Huang +2
This paper aims at enlarging the problem of Neural Architecture Search (NAS) from Single-Path and Multi-Path Search to automated Mixed-Path Search. In particular, we model the NAS…
NTIRE 2020 Challenge on Video Quality Mapping: Methods and Results
Dario Fuoli, Zhiwu Huang, Martin Danelljan +18
This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain. The chall…
Divide-and-Conquer Adversarial Learning for High-Resolution Image and Video Enhancement
Zhiwu Huang, Danda Pani Paudel, Guanju Li +3
This paper introduces a divide-and-conquer inspired adversarial learning (DACAL) approach for photo enhancement. The key idea is to decompose the photo enhancement process into hie…
Sliced Wasserstein Generative Models
Jiqing Wu, Zhiwu Huang, Dinesh Acharya +4
In generative modeling, the Wasserstein distance (WD) has emerged as a useful metric to measure the discrepancy between generated and real data distributions. Unfortunately, it is…
Towards High Resolution Video Generation with Progressive Growing of Sliced Wasserstein GANs
Dinesh Acharya, Zhiwu Huang, Danda Pani Paudel +1
The extension of image generation to video generation turns out to be a very difficult task, since the temporal dimension of videos introduces an extra challenge during the generat…
Covariance Pooling For Facial Expression Recognition
Dinesh Acharya, Zhiwu Huang, Danda Paudel +1
Classifying facial expressions into different categories requires capturing regional distortions of facial landmarks. We believe that second-order statistics such as covariance is…
Face Translation between Images and Videos using Identity-aware CycleGAN
Zhiwu Huang, Bernhard Kratzwald, Danda Pani Paudel +2
This paper presents a new problem of unpaired face translation between images and videos, which can be applied to facial video prediction and enhancement. In this problem there exi…