activity
20152026
most citedA Survey of Deep Learning-based Object Detection

1.3k citations · 1.4k across the 32 of their papers we have counts for

collaborators
Showing 2024Show all

16 papers · 1 filter

cs.NE2024

Knowledge-aware Evolutionary Graph Neural Architecture Search

Chao Wang, Jiaxuan Zhao, Lingling Li +4

Graph neural architecture search (GNAS) can customize high-performance graph neural network architectures for specific graph tasks or datasets. However, existing GNAS methods begin…

cs.LG2024★ 1 cited

Peri-midFormer: Periodic Pyramid Transformer for Time Series Analysis

Qiang Wu, Gechang Yao, Zhixi Feng +1

Time series analysis finds wide applications in fields such as weather forecasting, anomaly detection, and behavior recognition. Previous methods attempted to model temporal variat…

cs.CV2024★ 1 cited

SoccerNet 2024 Challenges Results

Anthony Cioppa, Silvio Giancola, Vladimir Somers +81

The SoccerNet 2024 challenges represent the fourth annual video understanding challenges organized by the SoccerNet team. These challenges aim to advance research across multiple t…

cs.CV2024★ 3 cited

Renormalized Connection for Scale-preferred Object Detection in Satellite Imagery

Fan Zhang, Lingling Li, Licheng Jiao +4

Satellite imagery, due to its long-range imaging, brings with it a variety of scale-preferred tasks, such as the detection of tiny/small objects, making the precise localization an…

cs.LG2024

Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation Classification

Xiaoyang Hao, Zhixi Feng, Tongqing Peng +1

Automatic modulation classification (AMC) is an effective way to deal with physical layer threats of the internet of things (IoT). However, there is often label mislabeling in prac…

cs.CV2024

Technique Report of CVPR 2024 PBDL Challenges

Ying Fu, Yu Li, Shaodi You +96

The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…

cs.CV2024

Fast and Efficient: Mask Neural Fields for 3D Scene Segmentation

Zihan Gao, Lingling Li, Licheng Jiao +5

Understanding 3D scenes is a crucial challenge in computer vision research with applications spanning multiple domains. Recent advancements in distilling 2D vision-language foundat…

cs.CV2024★ 1 cited

PVUW 2024 Challenge on Complex Video Understanding: Methods and Results

Henghui Ding, Chang Liu, Yunchao Wei +34

Pixel-level Video Understanding in the Wild Challenge (PVUW) focus on complex video understanding. In this CVPR 2024 workshop, we add two new tracks, Complex Video Object Segmentat…

cs.CV2024

3rd Place Solution for MOSE Track in CVPR 2024 PVUW workshop: Complex Video Object Segmentation

Xinyu Liu, Jing Zhang, Kexin Zhang +3

Video Object Segmentation (VOS) is a vital task in computer vision, focusing on distinguishing foreground objects from the background across video frames. Our work draws inspiratio…

cs.NE2024

Automatic Graph Topology-Aware Transformer

Chao Wang, Jiaxuan Zhao, Lingling Li +3

Existing efforts are dedicated to designing many topologies and graph-aware strategies for the graph Transformer, which greatly improve the model's representation capabilities. How…

cs.CV2024

Edit-Your-Motion: Space-Time Diffusion Decoupling Learning for Video Motion Editing

Yi Zuo, Lingling Li, Licheng Jiao +5

Existing diffusion-based methods have achieved impressive results in human motion editing. However, these methods often exhibit significant ghosting and body distortion in unseen i…

cs.CV2024

Exploring Beyond Logits: Hierarchical Dynamic Labeling Based on Embeddings for Semi-Supervised Classification

Yanbiao Ma, Licheng Jiao, Fang Liu +3

In semi-supervised learning, methods that rely on confidence learning to generate pseudo-labels have been widely proposed. However, increasing research finds that when faced with n…

cs.CV2024

Unveiling and Mitigating Generalized Biases of DNNs through the Intrinsic Dimensions of Perceptual Manifolds

Yanbiao Ma, Licheng Jiao, Fang Liu +5

Building fair deep neural networks (DNNs) is a crucial step towards achieving trustworthy artificial intelligence. Delving into deeper factors that affect the fairness of DNNs is p…

cs.CV2024

Heterogeneous Network Based Contrastive Learning Method for PolSAR Land Cover Classification

Jianfeng Cai, Yue Ma, Zhixi Feng +1

Polarimetric synthetic aperture radar (PolSAR) image interpretation is widely used in various fields. Recently, deep learning has made significant progress in PolSAR image classifi…

cs.CV2024★ 1 cited

Geometric Prior Guided Feature Representation Learning for Long-Tailed Classification

Yanbiao Ma, Licheng Jiao, Fang Liu +3

Real-world data are long-tailed, the lack of tail samples leads to a significant limitation in the generalization ability of the model. Although numerous approaches of class re-bal…

cs.NE2024★ 7 cited

When Large Language Models Meet Evolutionary Algorithms: Potential Enhancements and Challenges

Chao Wang, Jiaxuan Zhao, Licheng Jiao +3

Pre-trained large language models (LLMs) exhibit powerful capabilities for generating natural text. Evolutionary algorithms (EAs) can discover diverse solutions to complex real-wor…