676 citations · 4.7k across the 170 of their papers we have counts for
23 papers · 2 filters
Knowledge-Routed Visual Question Reasoning: Challenges for Deep Representation Embedding
Qingxing Cao, Bailin Li, Xiaodan Liang +2
Though beneficial for encouraging the Visual Question Answering (VQA) models to discover the underlying knowledge by exploiting the input-output correlation beyond image and text c…
AU-Expression Knowledge Constrained Representation Learning for Facial Expression Recognition
Tao Pu, Tianshui Chen, Yuan Xie +2
Recognizing human emotion/expressions automatically is quite an expected ability for intelligent robotics, as it can promote better communication and cooperation with humans. Curre…
Cross-Modal Collaborative Representation Learning and a Large-Scale RGBT Benchmark for Crowd Counting
Lingbo Liu, Jiaqi Chen, Hefeng Wu +3
Crowd counting is a fundamental yet challenging task, which desires rich information to generate pixel-wise crowd density maps. However, most previous methods only used the limited…
Auto-Panoptic: Cooperative Multi-Component Architecture Search for Panoptic Segmentation
Yangxin Wu, Gengwei Zhang, Hang Xu +2
Panoptic segmentation is posed as a new popular test-bed for the state-of-the-art holistic scene understanding methods with the requirement of simultaneously segmenting both foregr…
A Hamiltonian Monte Carlo Method for Probabilistic Adversarial Attack and Learning
Hongjun Wang, Guanbin Li, Xiaobai Liu +1
Although deep convolutional neural networks (CNNs) have demonstrated remarkable performance on multiple computer vision tasks, researches on adversarial learning have shown that de…
AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results
Pengxu Wei, Hannan Lu, Radu Timofte +68
This paper introduces the real image Super-Resolution (SR) challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with ECCV 2020. This ch…
Knowledge-Guided Multi-Label Few-Shot Learning for General Image Recognition
Tianshui Chen, Liang Lin, Riquan Chen +2
Recognizing multiple labels of an image is a practical yet challenging task, and remarkable progress has been achieved by searching for semantic regions and exploiting label depend…
Reinforcement Learning for Weakly Supervised Temporal Grounding of Natural Language in Untrimmed Videos
Jie Wu, Guanbin Li, Xiaoguang Han +1
Temporal grounding of natural language in untrimmed videos is a fundamental yet challenging multimedia task facilitating cross-media visual content retrieval. We focus on the weakl…
Collaborative Training between Region Proposal Localization and Classification for Domain Adaptive Object Detection
Ganlong Zhao, Guanbin Li, Ruijia Xu +1
Object detectors are usually trained with large amount of labeled data, which is expensive and labor-intensive. Pre-trained detectors applied to unlabeled dataset always suffer fro…
Online Alternate Generator against Adversarial Attacks
Haofeng Li, Yirui Zeng, Guanbin Li +2
The field of computer vision has witnessed phenomenal progress in recent years partially due to the development of deep convolutional neural networks. However, deep learning models…
Semantics-aware Adaptive Knowledge Distillation for Sensor-to-Vision Action Recognition
Yang Liu, Keze Wang, Guanbin Li +1
Existing vision-based action recognition is susceptible to occlusion and appearance variations, while wearable sensors can alleviate these challenges by capturing human motion with…
Component Divide-and-Conquer for Real-World Image Super-Resolution
Pengxu Wei, Ziwei Xie, Hannan Lu +4
In this paper, we present a large-scale Diverse Real-world image Super-Resolution dataset, i.e., DRealSR, as well as a divide-and-conquer Super-Resolution (SR) network, exploring t…
EagleEye: Fast Sub-net Evaluation for Efficient Neural Network Pruning
Bailin Li, Bowen Wu, Jiang Su +2
Finding out the computational redundant part of a trained Deep Neural Network (DNN) is the key question that pruning algorithms target on. Many algorithms try to predict model perf…
Adversarial Graph Representation Adaptation for Cross-Domain Facial Expression Recognition
Yuan Xie, Tianshui Chen, Tao Pu +2
Data inconsistency and bias are inevitable among different facial expression recognition (FER) datasets due to subjective annotating process and different collecting conditions. Re…
Cross-Domain Facial Expression Recognition: A Unified Evaluation Benchmark and Adversarial Graph Learning
Tianshui Chen, Tao Pu, Hefeng Wu +3
To address the problem of data inconsistencies among different facial expression recognition (FER) datasets, many cross-domain FER methods (CD-FERs) have been extensively devised i…
Fine-Grained Image Captioning with Global-Local Discriminative Objective
Jie Wu, Tianshui Chen, Hefeng Wu +3
Significant progress has been made in recent years in image captioning, an active topic in the fields of vision and language. However, existing methods tend to yield overly general…
Bidirectional Graph Reasoning Network for Panoptic Segmentation
Yangxin Wu, Gengwei Zhang, Yiming Gao +4
Recent researches on panoptic segmentation resort to a single end-to-end network to combine the tasks of instance segmentation and semantic segmentation. However, prior models only…
Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking
Hongjun Wang, Guangrun Wang, Ya Li +2
The success of DNNs has driven the extensive applications of person re-identification (ReID) into a new era. However, whether ReID inherits the vulnerability of DNNs remains unexpl…
Linguistically Driven Graph Capsule Network for Visual Question Reasoning
Qingxing Cao, Xiaodan Liang, Keze Wang +1
Recently, studies of visual question answering have explored various architectures of end-to-end networks and achieved promising results on both natural and synthetic datasets, whi…
Efficient Crowd Counting via Structured Knowledge Transfer
Lingbo Liu, Jiaqi Chen, Hefeng Wu +3
Crowd counting is an application-oriented task and its inference efficiency is crucial for real-world applications. However, most previous works relied on heavy backbone networks a…
DDet: Dual-path Dynamic Enhancement Network for Real-World Image Super-Resolution
Yukai Shi, Haoyu Zhong, Zhijing Yang +2
Different from traditional image super-resolution task, real image super-resolution(Real-SR) focus on the relationship between real-world high-resolution(HR) and low-resolution(LR)…
Depthwise Non-local Module for Fast Salient Object Detection Using a Single Thread
Haofeng Li, Guanbin Li, Binbin Yang +3
Recently deep convolutional neural networks have achieved significant success in salient object detection. However, existing state-of-the-art methods require high-end GPUs to achie…
Tree-Structured Policy based Progressive Reinforcement Learning for Temporally Language Grounding in Video
Jie Wu, Guanbin Li, Si Liu +1
Temporally language grounding in untrimmed videos is a newly-raised task in video understanding. Most of the existing methods suffer from inferior efficiency, lacking interpretabil…