65 citations · 102 across the 19 of their papers we have counts for
21 papers
Breaking Smooth-Motion Assumptions: A UAV Benchmark for Multi-Object Tracking in Complex and Adverse Conditions
Jingtao Ye, Kexin Zhang, Xunchi Ma +6
The rapid movements and agile maneuvers of unmanned aerial vehicles (UAVs) induce significant observational challenges for multi-object tracking (MOT). However, existing UAV-perspe…
FSD-CAP: Fractional Subgraph Diffusion with Class-Aware Propagation for Graph Feature Imputation
Xin Qiao, Shijie Sun, Anqi Dong +5
Imputing missing node features in graphs is challenging, particularly under high missing rates. Existing methods based on latent representations or global diffusion often fail to p…
VoteSplat: Hough Voting Gaussian Splatting for 3D Scene Understanding
Minchao Jiang, Shunyu Jia, Jiaming Gu +4
3D Gaussian Splatting (3DGS) has become horsepower in high-quality, real-time rendering for novel view synthesis of 3D scenes. However, existing methods focus primarily on geometri…
Intervening in Black Box: Concept Bottleneck Model for Enhancing Human Neural Network Mutual Understanding
Nuoye Xiong, Anqi Dong, Ning Wang +5
Recent advances in deep learning have led to increasingly complex models with deeper layers and more parameters, reducing interpretability and making their decisions harder to unde…
DailyDVS-200: A Comprehensive Benchmark Dataset for Event-Based Action Recognition
Qi Wang, Zhou Xu, Yuming Lin +6
Neuromorphic sensors, specifically event cameras, revolutionize visual data acquisition by capturing pixel intensity changes with exceptional dynamic range, minimal latency, and en…
Language Model Guided Interpretable Video Action Reasoning
Ning Wang, Guangming Zhu, HS Li +3
While neural networks have excelled in video action recognition tasks, their black-box nature often obscures the understanding of their decision-making processes. Recent approaches…
The two-way knowledge interaction interface between humans and neural networks
Zhanliang He, Nuoye Xiong, Hongsheng Li +3
Despite neural networks (NN) have been widely applied in various fields and generally outperforms humans, they still lack interpretability to a certain extent, and humans are unabl…
Content-Conditioned Generation of Stylized Free hand Sketches
Jiajun Liu, Siyuan Wang, Guangming Zhu +3
In recent years, the recognition of free-hand sketches has remained a popular task. However, in some special fields such as the military field, free-hand sketches are difficult to…
A multimodal gesture recognition dataset for desktop human-computer interaction
Qi Wang, Fengchao Zhu, Guangming Zhu +3
Gesture recognition is an indispensable component of natural and efficient human-computer interaction technology, particularly in desktop-level applications, where it can significa…
Flowmind2Digital: The First Comprehensive Flowmind Recognition and Conversion Approach
Huanyu Liu, Jianfeng Cai, Tingjia Zhang +6
Flowcharts and mind maps, collectively known as flowmind, are vital in daily activities, with hand-drawn versions facilitating real-time collaboration. However, there's a growing n…
Enhance Sketch Recognition's Explainability via Semantic Component-Level Parsing
Guangming Zhu, Siyuan Wang, Tianci Wu +1
Free-hand sketches are appealing for humans as a universal tool to depict the visual world. Humans can recognize varied sketches of a category easily by identifying the concurrence…
Sketch Input Method Editor: A Comprehensive Dataset and Methodology for Systematic Input Recognition
Guangming Zhu, Siyuan Wang, Qing Cheng +3
With the recent surge in the use of touchscreen devices, free-hand sketching has emerged as a promising modality for human-computer interaction. While previous research has focused…
UE4-NeRF:Neural Radiance Field for Real-Time Rendering of Large-Scale Scene
Jiaming Gu, Minchao Jiang, Hongsheng Li +5
Neural Radiance Fields (NeRF) is a novel implicit 3D reconstruction method that shows immense potential and has been gaining increasing attention. It enables the reconstruction of…
Spatial Parsing and Dynamic Temporal Pooling networks for Human-Object Interaction detection
Hongsheng Li, Guangming Zhu, Wu Zhen +5
The key of Human-Object Interaction(HOI) recognition is to infer the relationship between human and objects. Recently, the image's Human-Object Interaction(HOI) detection has made…
Scene Graph Generation: A Comprehensive Survey
Guangming Zhu, Liang Zhang, Youliang Jiang +8
Deep learning techniques have led to remarkable breakthroughs in the field of generic object detection and have spawned a lot of scene-understanding tasks in recent years. Scene gr…
Spatio-Temporal Interaction Graph Parsing Networks for Human-Object Interaction Recognition
Ning Wang, Guangming Zhu, Liang Zhang +3
For a given video-based Human-Object Interaction scene, modeling the spatio-temporal relationship between humans and objects are the important cue to understand the contextual info…
A Systematic Collection of Medical Image Datasets for Deep Learning
Johann Li, Guangming Zhu, Cong Hua +11
The astounding success made by artificial intelligence (AI) in healthcare and other fields proves that AI can achieve human-like performance. However, success always comes with cha…
Free-form Description Guided 3D Visual Graph Network for Object Grounding in Point Cloud
Mingtao Feng, Zhen Li, Qi Li +6
3D object grounding aims to locate the most relevant target object in a raw point cloud scene based on a free-form language description. Understanding complex and diverse descripti…
MeDaS: An open-source platform as service to help break the walls between medicine and informatics
Liang Zhang, Johann Li, Ping Li +7
In the past decade, deep learning (DL) has achieved unprecedented success in numerous fields including computer vision, natural language processing, and healthcare. In particular,…
Efficient Scene Text Detection with Textual Attention Tower
Liang Zhang, Yufei Liu, Hang Xiao +5
Scene text detection has received attention for years and achieved an impressive performance across various benchmarks. In this work, we propose an efficient and accurate approach…
Structure-Feature based Graph Self-adaptive Pooling
Liang Zhang, Xudong Wang, Hongsheng Li +6
Various methods to deal with graph data have been proposed in recent years. However, most of these methods focus on graph feature aggregation rather than graph pooling. Besides, th…