92 citations · 263 across the 15 of their papers we have counts for
15 papers
Implicit Fuzzification via Bounded Noise Injection for Robust Medical Image Segmentation
Bisheng Tang, Zhangfeng Ma, Chuchu Zhai +4
Image segmentation remains fundamentally limited by boundary ambiguity arising from sampling-induced information loss and inherent uncertainty in pixel-wise labeling. Although enco…
Lossless Point Cloud Attribute Compression Using Cross-scale, Cross-group, and Cross-color Prediction
Jianqiang Wang, Dandan Ding, Zhan Ma
This work extends the multiscale structure originally developed for point cloud geometry compression to point cloud attribute compression. To losslessly encode the attribute while…
QARV: Quantization-Aware ResNet VAE for Lossy Image Compression
Zhihao Duan, Ming Lu, Jack Ma +3
This paper addresses the problem of lossy image compression, a fundamental problem in image processing and information theory that is involved in many real-world applications. We s…
Dynamic Point Cloud Geometry Compression Using Multiscale Inter Conditional Coding
Jianqiang Wang, Dandan Ding, Hao Chen +1
This work extends the Multiscale Sparse Representation (MSR) framework developed for static Point Cloud Geometry Compression (PCGC) to support the dynamic PCGC through the use of m…
Efficient Visual Computing with Camera RAW Snapshots
Zhihao Li, Ming Lu, Xu Zhang +3
Conventional cameras capture image irradiance on a sensor and convert it to RGB images using an image signal processor (ISP). The images can then be used for photography or visual…
Rate-Distortion Optimized Post-Training Quantization for Learned Image Compression
Junqi Shi, Ming Lu, Zhan Ma
Quantizing a floating-point neural network to its fixed-point representation is crucial for Learned Image Compression (LIC) because it improves decoding consistency for interoperab…
CARNet:Compression Artifact Reduction for Point Cloud Attribute
Dandan Ding, Junzhe Zhang, Jianqiang Wang +1
A learning-based adaptive loop filter is developed for the Geometry-based Point Cloud Compression (G-PCC) standard to reduce attribute compression artifacts. The proposed method fi…
Efficient LiDAR Point Cloud Geometry Compression Through Neighborhood Point Attention
Ruixiang Xue, Jianqiang Wang, Zhan Ma
Although convolutional representation of multiscale sparse tensor demonstrated its superior efficiency to accurately model the occupancy probability for the compression of geometry…
Lossy Image Compression with Quantized Hierarchical VAEs
Zhihao Duan, Ming Lu, Zhan Ma +1
Recent research has shown a strong theoretical connection between variational autoencoders (VAEs) and the rate-distortion theory. Motivated by this, we consider the problem of loss…
Rendering Nighttime Image Via Cascaded Color and Brightness Compensation
Zhihao Li, Si Yi, Zhan Ma
Image signal processing (ISP) is crucial for camera imaging, and neural networks (NN) solutions are extensively deployed for daytime scenes. The lack of sufficient nighttime image…
Sparse Tensor-based Point Cloud Attribute Compression
Jianqiang Wang, Zhan Ma
Recently, numerous learning-based compression methods have been developed with outstanding performance for the coding of the geometry information of point clouds. On the contrary,…
High-Efficiency Lossy Image Coding Through Adaptive Neighborhood Information Aggregation
Ming Lu, Fangdong Chen, Shiliang Pu +1
Questing for learned lossy image coding (LIC) with superior compression performance and computation throughput is challenging. The vital factor behind it is how to intelligently ex…
Opening the Black Box of Learned Image Coders
Zhihao Duan, Ming Lu, Zhan Ma +1
End-to-end learned lossy image coders (LICs), as opposed to hand-crafted image codecs, have shown increasing superiority in terms of the rate-distortion performance. However, they…
Towards Robust Neural Image Compression: Adversarial Attack and Model Finetuning
Tong Chen, Zhan Ma
Deep neural network-based image compression has been extensively studied. However, the model robustness which is crucial to practical application is largely overlooked. We propose…
Sparse Tensor-based Multiscale Representation for Point Cloud Geometry Compression
Jianqiang Wang, Dandan Ding, Zhu Li +3
This study develops a unified Point Cloud Geometry (PCG) compression method through the processing of multiscale sparse tensor-based voxelized PCG. We call this compression method…