676 citations · 4.7k across the 170 of their papers we have counts for
173 papers
Dual-Perspective Semantic-Aware Representation Blending for Multi-Label Image Recognition with Partial Labels
Tao Pu, Tianshui Chen, Hefeng Wu +3
Despite achieving impressive progress, current multi-label image recognition (MLR) algorithms heavily depend on large-scale datasets with complete labels, making collecting large-s…
Semantic Representation and Dependency Learning for Multi-Label Image Recognition
Tao Pu, Mingzhan Sun, Hefeng Wu +3
Recently many multi-label image recognition (MLR) works have made significant progress by introducing pre-trained object detection models to generate lots of proposals or utilizing…
Unsupervised Domain Adaptive Salient Object Detection Through Uncertainty-Aware Pseudo-Label Learning
Pengxiang Yan, Ziyi Wu, Mengmeng Liu +3
Recent advances in deep learning significantly boost the performance of salient object detection (SOD) at the expense of labeling larger-scale per-pixel annotations. To relieve the…
Structured Semantic Transfer for Multi-Label Recognition with Partial Labels
Tianshui Chen, Tao Pu, Hefeng Wu +2
Multi-label image recognition is a fundamental yet practical task because real-world images inherently possess multiple semantic labels. However, it is difficult to collect large-s…
TCGL: Temporal Contrastive Graph for Self-supervised Video Representation Learning
Yang Liu, Keze Wang, Lingbo Liu +2
Video self-supervised learning is a challenging task, which requires significant expressive power from the model to leverage rich spatial-temporal knowledge and generate effective…
Aerial Images Meet Crowdsourced Trajectories: A New Approach to Robust Road Extraction
Lingbo Liu, Zewei Yang, Guanbin Li +3
Land remote sensing analysis is a crucial research in earth science. In this work, we focus on a challenging task of land analysis, i.e., automatic extraction of traffic roads from…
Image Comes Dancing with Collaborative Parsing-Flow Video Synthesis
Bowen Wu, Zhenyu Xie, Xiaodan Liang +3
Transferring human motion from a source to a target person poses great potential in computer vision and graphics applications. A crucial step is to manipulate sequential future mot…
Wav-BERT: Cooperative Acoustic and Linguistic Representation Learning for Low-Resource Speech Recognition
Guolin Zheng, Yubei Xiao, Ke Gong +3
Unifying acoustic and linguistic representation learning has become increasingly crucial to transfer the knowledge learned on the abundance of high-resource language data for low-r…
Road Network Guided Fine-Grained Urban Traffic Flow Inference
Lingbo Liu, Mengmeng Liu, Guanbin Li +3
Accurate inference of fine-grained traffic flow from coarse-grained one is an emerging yet crucial problem, which can help greatly reduce the number of the required traffic monitor…
Trash to Treasure: Harvesting OOD Data with Cross-Modal Matching for Open-Set Semi-Supervised Learning
Junkai Huang, Chaowei Fang, Weikai Chen +5
Open-set semi-supervised learning (open-set SSL) investigates a challenging but practical scenario where out-of-distribution (OOD) samples are contained in the unlabeled data. Whil…
Weakly-Supervised Spatio-Temporal Anomaly Detection in Surveillance Video
Jie Wu, Wei Zhang, Guanbin Li +5
In this paper, we introduce a novel task, referred to as Weakly-Supervised Spatio-Temporal Anomaly Detection (WSSTAD) in surveillance video. Specifically, given an untrimmed video,…
Towards Quantifiable Dialogue Coherence Evaluation
Zheng Ye, Liucun Lu, Lishan Huang +2
Automatic dialogue coherence evaluation has attracted increasing attention and is crucial for developing promising dialogue systems. However, existing metrics have two major limita…
Prototypical Graph Contrastive Learning
Shuai Lin, Pan Zhou, Zi-Yuan Hu +6
Graph-level representations are critical in various real-world applications, such as predicting the properties of molecules. But in practice, precise graph annotations are generall…
GeoQA: A Geometric Question Answering Benchmark Towards Multimodal Numerical Reasoning
Jiaqi Chen, Jianheng Tang, Jinghui Qin +4
Automatic math problem solving has recently attracted increasing attention as a long-standing AI benchmark. In this paper, we focus on solving geometric problems, which requires a…
Solving Inefficiency of Self-supervised Representation Learning
Guangrun Wang, Keze Wang, Guangcong Wang +2
Self-supervised learning (especially contrastive learning) has attracted great interest due to its huge potential in learning discriminative representations in an unsupervised mann…
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition
Guangrun Wang, Liang Lin, Rongcong Chen +2
Current state-of-the-art visual recognition systems usually rely on the following pipeline: (a) pretraining a neural network on a large-scale dataset (e.g., ImageNet) and (b) finet…
Learning Class-Agnostic Pseudo Mask Generation for Box-Supervised Semantic Segmentation
Chaohao Xie, Dongwei Ren, Lei Wang +1
Recently, several weakly supervised learning methods have been devoted to utilize bounding box supervision for training deep semantic segmentation models. Most existing methods usu…
GTAE: Graph-Transformer based Auto-Encoders for Linguistic-Constrained Text Style Transfer
Yukai Shi, Sen Zhang, Chenxing Zhou +3
Non-parallel text style transfer has attracted increasing research interests in recent years. Despite successes in transferring the style based on the encoder-decoder framework, cu…
Unifying Relational Sentence Generation and Retrieval for Medical Image Report Composition
Fuyu Wang, Xiaodan Liang, Lin Xu +1
Beyond generating long and topic-coherent paragraphs in traditional captioning tasks, the medical image report composition task poses more task-oriented challenges by requiring bot…
Graph-Evolving Meta-Learning for Low-Resource Medical Dialogue Generation
Shuai Lin, Pan Zhou, Xiaodan Liang +4
Human doctors with well-structured medical knowledge can diagnose a disease merely via a few conversations with patients about symptoms. In contrast, existing knowledge-grounded di…
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…
REM-Net: Recursive Erasure Memory Network for Commonsense Evidence Refinement
Yinya Huang, Meng Fang, Xunlin Zhan +3
When answering a question, people often draw upon their rich world knowledge in addition to the particular context. While recent works retrieve supporting facts/evidence from commo…
Adversarial Meta Sampling for Multilingual Low-Resource Speech Recognition
Yubei Xiao, Ke Gong, Pan Zhou +3
Low-resource automatic speech recognition (ASR) is challenging, as the low-resource target language data cannot well train an ASR model. To solve this issue, meta-learning formulat…