67 citations · 80 across the 18 of their papers we have counts for
21 papers
Locality-Aware Density Control for Efficient Gaussian-based Image Representation
Jiacong Chen, Qingyu Mao, Xiandong Meng +5
2D Gaussian Splatting is an attractive direction for image representation due to its explicit formulation, fast rasterization, and favorable decoding efficiency. The representation…
Shift-MoE-Based DJSCC for CSI Feedback in Multi-User Pinching-Antenna Systems
Jian Zou, Yifan Lian, Yongsheng Liang +4
In frequency-division duplexing systems, the performance gains of pinching-antenna systems (PASS) critically depend on accurate channel state information (CSI) at the base station.…
STGV: Spatio-Temporal Hash Encoding for Gaussian-based Video Representation
Jierun Lin, Jiacong Chen, Qingyu Mao +4
2D Gaussian Splatting (2DGS) has recently become a promising paradigm for high-quality video representation. However, existing methods employ content-agnostic or spatio-temporal fe…
Robust Deep Joint Source-Channel Coding for Video Transmission over Multipath Fading Channel
Bohuai Xiao, Jian Zou, Fanyang Meng +2
To address the challenges of wireless video transmission over multipath fading channels, we propose a robust deep joint source-channel coding (DeepJSCC) framework by effectively ex…
Boosting Neural Video Representation via Online Structural Reparameterization
Ziyi Li, Qingyu Mao, Shuai Liu +3
Neural Video Representation~(NVR) is a promising paradigm for video compression, showing great potential in improving video storage and transmission efficiency. While recent advanc…
Motion Matters: Compact Gaussian Streaming for Free-Viewpoint Video Reconstruction
Jiacong Chen, Qingyu Mao, Youneng Bao +4
3D Gaussian Splatting (3DGS) has emerged as a high-fidelity and efficient paradigm for online free-viewpoint video (FVV) reconstruction, offering viewers rapid responsiveness and i…
Content-Distortion High-Order Interaction for Blind Image Quality Assessment
Shuai Liu, Qingyu Mao, Chao Li +4
The content and distortion are widely recognized as the two primary factors affecting the visual quality of an image. While existing No-Reference Image Quality Assessment (NR-IQA)…
Enhancing Adversarial Training with Prior Knowledge Distillation for Robust Image Compression
Zhi Cao, Youneng Bao, Fanyang Meng +4
Deep neural network-based image compression (NIC) has achieved excellent performance, but NIC method models have been shown to be susceptible to backdoor attacks. Adversarial train…
Learning Mutual Excitation for Hand-to-Hand and Human-to-Human Interaction Recognition
Mengyuan Liu, Chen Chen, Songtao Wu +2
Recognizing interactive actions, including hand-to-hand interaction and human-to-human interaction, has attracted increasing attention for various applications in the field of vide…
Explore Human Parsing Modality for Action Recognition
Jinfu Liu, Runwei Ding, Yuhang Wen +4
Multimodal-based action recognition methods have achieved high success using pose and RGB modality. However, skeletons sequences lack appearance depiction and RGB images suffer irr…
Dynamic Compositional Graph Convolutional Network for Efficient Composite Human Motion Prediction
Wanying Zhang, Shen Zhao, Fanyang Meng +2
With potential applications in fields including intelligent surveillance and human-robot interaction, the human motion prediction task has become a hot research topic and also has…
Integrating Human Parsing and Pose Network for Human Action Recognition
Runwei Ding, Yuhang Wen, Jinfu Liu +3
Human skeletons and RGB sequences are both widely-adopted input modalities for human action recognition. However, skeletons lack appearance features and color data suffer large amo…
Universal Learned Image Compression With Low Computational Cost
Bowen Li, Yao Xin, Youneng Bao +3
Recently, learned image compression methods have developed rapidly and exhibited excellent rate-distortion performance when compared to traditional standards, such as JPEG, JPEG200…
Context-aware Visual Tracking with Joint Meta-updating
Qiuhong Shen, Xin Li, Fanyang Meng +1
Visual object tracking acts as a pivotal component in various emerging video applications. Despite the numerous developments in visual tracking, existing deep trackers are still li…
Exploring Structural Sparsity in Neural Image Compression
Shanzhi Yin, Chao Li, Wen Tan +3
Neural image compression have reached or out-performed traditional methods (such as JPEG, BPG, WebP). However,their sophisticated network structures with cascaded convolution layer…
Universal Efficient Variable-rate Neural Image Compression
Shanzhi Yin, Chao Li, Youneng Bao +1
Recently, Learning-based image compression has reached comparable performance with traditional image codecs(such as JPEG, BPG, WebP). However, computational complexity and rate fle…
Cloth Interactive Transformer for Virtual Try-On
Bin Ren, Hao Tang, Fanyang Meng +3
The 2D image-based virtual try-on has aroused increased interest from the multimedia and computer vision fields due to its enormous commercial value. Nevertheless, most existing im…
TCDesc: Learning Topology Consistent Descriptors for Image Matching
Honghu Pan, Fanyang Meng, Nana Fan +1
The constraint of neighborhood consistency or local consistency is widely used for robust image matching. In this paper, we focus on learning neighborhood topology consistent descr…
TCDesc: Learning Topology Consistent Descriptors
Honghu Pan, Fanyang Meng, Zhenyu He +2
Triplet loss is widely used for learning local descriptors from image patch. However, triplet loss only minimizes the Euclidean distance between matching descriptors and maximizes…
Bi-directional Exponential Angular Triplet Loss for RGB-Infrared Person Re-Identification
Hanrong Ye, Hong Liu, Fanyang Meng +1
RGB-Infrared person re-identification (RGB-IR Re- ID) is a cross-modality matching problem, where the modality discrepancy is a big challenge. Most existing works use Euclidean met…
A Bidirectional Adaptive Bandwidth Mean Shift Strategy for Clustering
Fanyang Meng, Hong Liu, Yongsheng Liang +2
The bandwidth of a kernel function is a crucial parameter in the mean shift algorithm. This paper proposes a novel adaptive bandwidth strategy which contains three main contributio…