262 citations · 1.9k across the 68 of their papers we have counts for
69 papers
Perceptual Video Coding for Machines via Satisfied Machine Ratio Modeling
Qi Zhang, Shanshe Wang, Xinfeng Zhang +4
Video Coding for Machines (VCM) aims to compress visual signals for machine analysis. However, existing methods only consider a few machines, neglecting the majority. Moreover, the…
Cross Modal Compression: Towards Human-comprehensible Semantic Compression
Jiguo Li, Chuanmin Jia, Xinfeng Zhang +2
Traditional image/video compression aims to reduce the transmission/storage cost with signal fidelity as high as possible. However, with the increasing demand for machine analysis…
Towards Hybrid-Optimization Video Coding
Shuai Huo, Dong Liu, Li Li +3
Video coding is a mathematical optimization problem of rate and distortion essentially. To solve this complex optimization problem, two popular video coding frameworks have been de…
STIP: A SpatioTemporal Information-Preserving and Perception-Augmented Model for High-Resolution Video Prediction
Zheng Chang, Xinfeng Zhang, Shanshe Wang +2
Although significant achievements have been achieved by recurrent neural network (RNN) based video prediction methods, their performance in datasets with high resolutions is still…
Hierarchical Similarity Learning for Aliasing Suppression Image Super-Resolution
Yuqing Liu, Qi Jia, Jian Zhang +4
As a highly ill-posed issue, single image super-resolution (SISR) has been widely investigated in recent years. The main task of SISR is to recover the information loss caused by t…
Learning Weighting Map for Bit-Depth Expansion within a Rational Range
Yuqing Liu, Qi Jia, Jian Zhang +4
Bit-depth expansion (BDE) is one of the emerging technologies to display high bit-depth (HBD) image from low bit-depth (LBD) source. Existing BDE methods have no unified solution f…
STAU: A SpatioTemporal-Aware Unit for Video Prediction and Beyond
Zheng Chang, Xinfeng Zhang, Shanshe Wang +2
Video prediction aims to predict future frames by modeling the complex spatiotemporal dynamics in videos. However, most of the existing methods only model the temporal information…
STRPM: A Spatiotemporal Residual Predictive Model for High-Resolution Video Prediction
Zheng Chang, Xinfeng Zhang, Shanshe Wang +2
Although many video prediction methods have obtained good performance in low-resolution (64128) videos, predictive models for high-resolution (5124K) videos have not be…
P-STMO: Pre-Trained Spatial Temporal Many-to-One Model for 3D Human Pose Estimation
Wenkang Shan, Zhenhua Liu, Xinfeng Zhang +3
This paper introduces a novel Pre-trained Spatial Temporal Many-to-One (P-STMO) model for 2D-to-3D human pose estimation task. To reduce the difficulty of capturing spatial and tem…
Cross-SRN: Structure-Preserving Super-Resolution Network with Cross Convolution
Yuqing Liu, Qi Jia, Xin Fan +3
It is challenging to restore low-resolution (LR) images to super-resolution (SR) images with correct and clear details. Existing deep learning works almost neglect the inherent str…
Towards End-to-End Image Compression and Analysis with Transformers
Yuanchao Bai, Xu Yang, Xianming Liu +4
We propose an end-to-end image compression and analysis model with Transformers, targeting to the cloud-based image classification application. Instead of placing an existing Trans…
Video-based Point Cloud Compression Artifact Removal
Anique Akhtar, Wen Gao, Li Li +3
Photo-realistic point cloud capture and transmission are the fundamental enablers for immersive visual communication. The coding process of dynamic point clouds, especially video-b…
Improving Robustness and Accuracy via Relative Information Encoding in 3D Human Pose Estimation
Wenkang Shan, Haopeng Lu, Shanshe Wang +2
Most of the existing 3D human pose estimation approaches mainly focus on predicting 3D positional relationships between the root joint and other human joints (local motion) instead…
Post-Training Quantization for Vision Transformer
Zhenhua Liu, Yunhe Wang, Kai Han +2
Recently, transformer has achieved remarkable performance on a variety of computer vision applications. Compared with mainstream convolutional neural networks, vision transformers…
Progressive Stage-wise Learning for Unsupervised Feature Representation Enhancement
Zefan Li, Chenxi Liu, Alan Yuille +3
Unsupervised learning methods have recently shown their competitiveness against supervised training. Typically, these methods use a single objective to train the entire network. Bu…
Rate Distortion Characteristic Modeling for Neural Image Compression
Chuanmin Jia, Ziqing Ge, Shanshe Wang +2
End-to-end optimized neural image compression (NIC) has obtained superior lossy compression performance recently. In this paper, we consider the problem of rate-distortion (R-D) ch…
Recent Standard Development Activities on Video Coding for Machines
Wen Gao, Shan Liu, Xiaozhong Xu +3
In recent years, video data has dominated internet traffic and becomes one of the major data formats. With the emerging 5G and internet of things (IoT) technologies, more and more…
Sub-sampled Cross-component Prediction for Emerging Video Coding Standards
Junru Li, Meng Wang, Li Zhang +5
Cross-component linear model (CCLM) prediction has been repeatedly proven to be effective in reducing the inter-channel redundancies in video compression. Essentially speaking, the…
Intrinsic Temporal Regularization for High-resolution Human Video Synthesis
Lingbo Yang, Zhanning Gao, Peiran Ren +2
Temporal consistency is crucial for extending image processing pipelines to the video domain, which is often enforced with flow-based warping error over adjacent frames. Yet for hu…
Pre-Trained Image Processing Transformer
Hanting Chen, Yunhe Wang, Tianyu Guo +7
As the computing power of modern hardware is increasing strongly, pre-trained deep learning models (e.g., BERT, GPT-3) learned on large-scale datasets have shown their effectivenes…
Implicit Subspace Prior Learning for Dual-Blind Face Restoration
Lingbo Yang, Pan Wang, Zhanning Gao +4
Face restoration is an inherently ill-posed problem, where additional prior constraints are typically considered crucial for mitigating such pathology. However, real-world image pr…
Assessing the Quality-of-Experience of Adaptive Bitrate Video Streaming
Zhengfang Duanmu, Wentao Liu, Zhuoran Li +4
The diversity of video delivery pipeline poses a grand challenge to the evaluation of adaptive bitrate (ABR) streaming algorithms and objective quality-of-experience (QoE) models.…
Sequential Hierarchical Learning with Distribution Transformation for Image Super-Resolution
Yuqing Liu, Xinfeng Zhang, Shanshe Wang +2
Multi-scale design has been considered in recent image super-resolution (SR) works to explore the hierarchical feature information. Existing multi-scale networks aim to build elabo…
Region-adaptive Texture Enhancement for Detailed Person Image Synthesis
Lingbo Yang, Pan Wang, Xinfeng Zhang +6
The ability to produce convincing textural details is essential for the fidelity of synthesized person images. However, existing methods typically follow a ``warping-based'' strate…