93 citations · 426 across the 24 of their papers we have counts for
24 papers
Tuning Pre-trained Model via Moment Probing
Mingze Gao, Qilong Wang, Zhenyi Lin +3
Recently, efficient fine-tuning of large-scale pre-trained models has attracted increasing research interests, where linear probing (LP) as a fundamental module is involved in expl…
Multi-modal Gated Mixture of Local-to-Global Experts for Dynamic Image Fusion
Yiming Sun, Bing Cao, Pengfei Zhu +1
Infrared and visible image fusion aims to integrate comprehensive information from multiple sources to achieve superior performances on various practical tasks, such as detection,…
Unsupervised Self-Driving Attention Prediction via Uncertainty Mining and Knowledge Embedding
Pengfei Zhu, Mengshi Qi, Xia Li +2
Predicting attention regions of interest is an important yet challenging task for self-driving systems. Existing methodologies rely on large-scale labeled traffic datasets that are…
HS-Diffusion: Semantic-Mixing Diffusion for Head Swapping
Qinghe Wang, Lijie Liu, Miao Hua +5
Image-based head swapping task aims to stitch a source head to another source body flawlessly. This seldom-studied task faces two major challenges: 1) Preserving the head and body…
Latent Heterogeneous Graph Network for Incomplete Multi-View Learning
Pengfei Zhu, Xinjie Yao, Yu Wang +4
Multi-view learning has progressed rapidly in recent years. Although many previous studies assume that each instance appears in all views, it is common in real-world applications f…
Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding
Junwen Pan, Guanlin Chen, Yi Liu +4
Answer grounding aims to reveal the visual evidence for visual question answering (VQA), which entails highlighting relevant positions in the image when answering questions about i…
Learning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation
Junwen Pan, Pengfei Zhu, Kaihua Zhang +5
Semantic segmentation with limited annotations, such as weakly supervised semantic segmentation (WSSS) and semi-supervised semantic segmentation (SSSS), is a challenging task that…
Label-efficient Hybrid-supervised Learning for Medical Image Segmentation
Junwen Pan, Qi Bi, Yanzhan Yang +2
Due to the lack of expertise for medical image annotation, the investigation of label-efficient methodology for medical image segmentation becomes a heated topic. Recent progresses…
Learning Dynamic Compact Memory Embedding for Deformable Visual Object Tracking
Pengfei Zhu, Hongtao Yu, Kaihua Zhang +5
Recently, template-based trackers have become the leading tracking algorithms with promising performance in terms of efficiency and accuracy. However, the correlation operation bet…
Unsupervised Open-Domain Question Answering
Pengfei Zhu, Xiaoguang Li, Jian Li +1
Open-domain Question Answering (ODQA) has achieved significant results in terms of supervised learning manner. However, data annotation cannot also be irresistible for its huge dem…
VisDrone-CC2020: The Vision Meets Drone Crowd Counting Challenge Results
Dawei Du, Longyin Wen, Pengfei Zhu +52
Crowd counting on the drone platform is an interesting topic in computer vision, which brings new challenges such as small object inference, background clutter and wide viewpoint.…
Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark
Longyin Wen, Dawei Du, Pengfei Zhu +4
To promote the developments of object detection, tracking and counting algorithms in drone-captured videos, we construct a benchmark with a new drone-captured largescale dataset, n…
Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
Binyuan Hui, Ruiying Geng, Qiyu Ren +7
Semantic parsing has long been a fundamental problem in natural language processing. Recently, cross-domain context-dependent semantic parsing has become a new focus of research. C…
SPL-MLL: Selecting Predictable Landmarks for Multi-Label Learning
Junbing Li, Changqing Zhang, Pengfei Zhu +3
Although significant progress achieved, multi-label classification is still challenging due to the complexity of correlations among different labels. Furthermore, modeling the rela…
Multi-Drone based Single Object Tracking with Agent Sharing Network
Pengfei Zhu, Jiayu Zheng, Dawei Du +3
Drone equipped with cameras can dynamically track the target in the air from a broader view compared with static cameras or moving sensors over the ground. However, it is still cha…
Spatial Attention Pyramid Network for Unsupervised Domain Adaptation
Congcong Li, Dawei Du, Libo Zhang +4
Unsupervised domain adaptation is critical in various computer vision tasks, such as object detection, instance segmentation, and semantic segmentation, which aims to alleviate per…
Rethinking Object Detection in Retail Stores
Yuanqiang Cai, Longyin Wen, Libo Zhang +2
The convention standard for object detection uses a bounding box to represent each individual object instance. However, it is not practical in the industry-relevant applications in…
Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning
Yiming Sun, Bing Cao, Pengfei Zhu +1
Drone-based vehicle detection aims at finding the vehicle locations and categories in an aerial image. It empowers smart city traffic management and disaster rescue. Researchers ha…
DUMA: Reading Comprehension with Transposition Thinking
Pengfei Zhu, Hai Zhao, Xiaoguang Li
Multi-choice Machine Reading Comprehension (MRC) requires model to decide the correct answer from a set of answer options when given a passage and a question. Thus in addition to a…
Detection and Tracking Meet Drones Challenge
Pengfei Zhu, Longyin Wen, Dawei Du +4
Drones, or general UAVs, equipped with cameras have been fast deployed with a wide range of applications, including agriculture, aerial photography, and surveillance. Consequently,…
Drone-based Joint Density Map Estimation, Localization and Tracking with Space-Time Multi-Scale Attention Network
Longyin Wen, Dawei Du, Pengfei Zhu +4
This paper proposes a space-time multi-scale attention network (STANet) to solve density map estimation, localization and tracking in dense crowds of video clips captured by drones…
Multi-view Deep Subspace Clustering Networks
Pengfei Zhu, Xinjie Yao, Yu Wang +3
Multi-view subspace clustering aims to discover the inherent structure of data by fusing multiple views of complementary information. Most existing methods first extract multiple t…
On Improving Deep Reinforcement Learning for POMDPs
Pengfei Zhu, Xin Li, Pascal Poupart +1
Deep Reinforcement Learning (RL) recently emerged as one of the most competitive approaches for learning in sequential decision making problems with fully observable environments,…
On Improving Deep Reinforcement Learning for POMDPs
Pengfei Zhu, Xin Li, Pascal Poupart +1
Deep Reinforcement Learning (RL) recently emerged as one of the most competitive approaches for learning in sequential decision making problems with fully observable environments,…