activity
20172023
most citedLearning Self-Supervised Low-Rank Network for Single-Stage Weakly and Semi-Supervised Semantic Segmentation

93 citations · 426 across the 24 of their papers we have counts for

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17 papers · 1 filter

cs.CV2023

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…

cs.CV2023★ 3 cited

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,…

cs.CV2023

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…

cs.CV2022★ 1 cited

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…

cs.CV2022

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…

cs.CV2022★ 93 cited

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…

cs.CV2021

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…

cs.CV2021

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.…

cs.CV2021★ 8 cited

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…

cs.CV2020★ 3 cited

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…

cs.CV2020★ 1 cited

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…

cs.CV2020★ 7 cited

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…

cs.CV2020★ 6 cited

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…

cs.CV2020★ 5 cited

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…

cs.CV2020★ 14 cited

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,…

cs.CV2019★ 27 cited

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…

cs.CV2019★ 51 cited

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…