321 citations · 1.8k across the 66 of their papers we have counts for
20 papers · 1 filter
Fully Context-Aware Image Inpainting with a Learned Semantic Pyramid
Wendong Zhang, Yunbo Wang, Bingbing Ni +1
Restoring reasonable and realistic content for arbitrary missing regions in images is an important yet challenging task. Although recent image inpainting models have made significa…
TAL: Two-stream Adaptive Learning for Generalizable Person Re-identification
Yichao Yan, Junjie Li, Shengcai Liao +3
Domain generalizable person re-identification aims to apply a trained model to unseen domains. Prior works either combine the data in all the training domains to capture domain-inv…
Out-of-Domain Human Mesh Reconstruction via Dynamic Bilevel Online Adaptation
Shanyan Guan, Jingwei Xu, Michelle Z. He +3
We consider a new problem of adapting a human mesh reconstruction model to out-of-domain streaming videos, where performance of existing SMPL-based models are significantly affecte…
ZARTS: On Zero-order Optimization for Neural Architecture Search
Xiaoxing Wang, Wenxuan Guo, Junchi Yan +2
Differentiable architecture search (DARTS) has been a popular one-shot paradigm for NAS due to its high efficiency. It introduces trainable architecture parameters to represent the…
DAAS: Differentiable Architecture and Augmentation Policy Search
Xiaoxing Wang, Xiangxiang Chu, Junchi Yan +1
Neural architecture search (NAS) has been an active direction of automatic machine learning (Auto-ML), aiming to explore efficient network structures. The searched architecture is…
Efficient Person Search: An Anchor-Free Approach
Yichao Yan, Jinpeng Li, Jie Qin +2
Person search aims to simultaneously localize and identify a query person from realistic, uncropped images. To achieve this goal, state-of-the-art models typically add a re-id bran…
Learning to Track Objects from Unlabeled Videos
Jilai Zheng, Chao Ma, Houwen Peng +1
In this paper, we propose to learn an Unsupervised Single Object Tracker (USOT) from scratch. We identify that three major challenges, i.e., moving object discovery, rich temporal…
Angel's Girl for Blind Painters: an Efficient Painting Navigation System Validated by Multimodal Evaluation Approach
Hang Liu, Menghan Hu, Yuzhen Chen +5
For people who ardently love painting but unfortunately have visual impairments, holding a paintbrush to create a work is a very difficult task. People in this special group are ea…
Local-to-Global Self-Attention in Vision Transformers
Jinpeng Li, Yichao Yan, Shengcai Liao +2
Transformers have demonstrated great potential in computer vision tasks. To avoid dense computations of self-attentions in high-resolution visual data, some recent Transformer mode…
Task-Specific Normalization for Continual Learning of Blind Image Quality Models
Weixia Zhang, Kede Ma, Guangtao Zhai +1
In this paper, we present a simple yet effective continual learning method for blind image quality assessment (BIQA) with improved quality prediction accuracy, plasticity-stability…
Context-Aware Image Inpainting with Learned Semantic Priors
Wendong Zhang, Junwei Zhu, Ying Tai +5
Recent advances in image inpainting have shown impressive results for generating plausible visual details on rather simple backgrounds. However, for complex scenes, it is still cha…
Making CNNs Interpretable by Building Dynamic Sequential Decision Forests with Top-down Hierarchy Learning
Yilin Wang, Shaozuo Yu, Xiaokang Yang +1
In this paper, we propose a generic model transfer scheme to make Convlutional Neural Networks (CNNs) interpretable, while maintaining their high classification accuracy. We achiev…
Exploring Visual Context for Weakly Supervised Person Search
Yichao Yan, Jinpeng Li, Shengcai Liao +4
Person search has recently emerged as a challenging task that jointly addresses pedestrian detection and person re-identification. Existing approaches follow a fully supervised set…
A Bi-Level Framework for Learning to Solve Combinatorial Optimization on Graphs
Runzhong Wang, Zhigang Hua, Gan Liu +6
Combinatorial Optimization (CO) has been a long-standing challenging research topic featured by its NP-hard nature. Traditionally such problems are approximately solved with heuris…
Learning Multi-Attention Context Graph for Group-Based Re-Identification
Yichao Yan, Jie Qin, Bingbing Ni +6
Learning to re-identify or retrieve a group of people across non-overlapped camera systems has important applications in video surveillance. However, most existing methods focus on…
Bilevel Online Adaptation for Out-of-Domain Human Mesh Reconstruction
Shanyan Guan, Jingwei Xu, Yunbo Wang +2
This paper considers a new problem of adapting a pre-trained model of human mesh reconstruction to out-of-domain streaming videos. However, most previous methods based on the param…
IoU Attack: Towards Temporally Coherent Black-Box Adversarial Attack for Visual Object Tracking
Shuai Jia, Yibing Song, Chao Ma +1
Adversarial attack arises due to the vulnerability of deep neural networks to perceive input samples injected with imperceptible perturbations. Recently, adversarial attack has bee…
Learning Comprehensive Motion Representation for Action Recognition
Mingyu Wu, Boyuan Jiang, Donghao Luo +7
For action recognition learning, 2D CNN-based methods are efficient but may yield redundant features due to applying the same 2D convolution kernel to each frame. Recent efforts at…
Continual Learning for Blind Image Quality Assessment
Weixia Zhang, Dingquan Li, Chao Ma +3
The explosive growth of image data facilitates the fast development of image processing and computer vision methods for emerging visual applications, meanwhile introducing novel di…
Learning Interpretable Deep State Space Model for Probabilistic Time Series Forecasting
Longyuan Li, Junchi Yan, Xiaokang Yang +1
Probabilistic time series forecasting involves estimating the distribution of future based on its history, which is essential for risk management in downstream decision-making. We…