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检索条件"任意字段=2023 IEEE International Conference on Visual Communications and Image Processing, VCIP 2023"

共 2299 条记录，以下是271-280 订阅

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BRIGHTNESS PRESERVING VIDEO CONTRAST ENHANCEMENT USING S-SHAPED TRANSFER FUNCTION

BRIGHTNESS PRESERVING VIDEO CONTRAST ENHANCEMENT USING S-SHA...

引用

ieee international conference on visual communications and image processing (vcip)

作者： Gu, Ke Zhai, Guangtao Liu, Min Min, Xiongkuo Yang, Xiaokang Zhang, Wenjun Shanghai Jiao Tong Univ Inst Image Commun & Informat Proc Shanghai 200030 Peoples R China Shanghai Key Lab Digital Media Proc Shanghai 200030 Peoples R China

ISBN: (纸本)9781479902880

This paper presents an efficient perceptual model inspired efficient video contrast enhancement algorithm. We propose a S-shaped transfer function for image pixel values that effectively improves the perceived contrast while preserving brightness of the scene. The S-shaped transfer function has only one control parameter that can be adaptively chosen for different video contents, such as sports, cartoon, news, and landscape programs. Then, the input image brightness is further preserved, in order to maintain the perception of human visual system (HVS) to some special scenes, such as dark scene and seaside scene. Experiments and comparative study on VQEG Phase I test database demonstrate that the proposed S-shaped Transfer function based Brightness Preserving (STBP) contrast enhancement algorithm outperforms various histogram equalization based methods such as HE, DSIHE, RSIHE and WTHE, yet with much lower computational complexity.

关键词： Video contrast enhancement S-shaped transfer curves human visual system (HVS) video scenes brightness preservation

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Learned image Compression with Enhanced Dynamic Spatial Aggregation and Asymmetric Entropy model

Learned Image Compression with Enhanced Dynamic Spatial Aggr...

引用

2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Zhang, Yuanton Fu, Nianxiang Yu, Guo Lv, Xiangdong Wang, Huairui Chen, Zhenzhong Wuhan University School of Remote Sensing and Information Engineering Wuhan China Wuhan University Hubei Luojia Laboratory Wuhan China Wuhan University School of Computer Science Wuhan China

ISBN: (纸本)9798350359855

Learned image compression (LIC) has shown significant potential and better rate-distortion performance than traditional techniques. However, existing CNN-based approaches or window-based self-Attention methods can only capture spatial information within fixed ranges. To tackle this limitation, we propose a novel method with dynamic spatial aggregation for transform coding. Our approach introduces enhanced adaptive aggregation, which generates kernel offsets to capture relevant information within content-dependent ranges, improving the transform process. Furthermore, we define a generalized coarse-To-fine entropy model that considers global context, channel-wise information, and spatial context in a coarse-To-fine manner. Additionally, our method takes into full consideration the model's efficiency and complexity. By introducing the asymmetric entropy model structure and efficient heterogeneous convolution, our approach maintains lower coding complexity and higher decoding speed while ensuring performance. Experimental results demonstrate a substantial improvement in rate-distortion performance achieved by our method when compared to traditional compression methods like VTM and BPG, as well as some LIC methods. © 2023 ieee.

关键词： image compression

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DENSE DEPTH ACQUISITION VIA ONE-SHOT STRIPE STRUCTURED LIGHT

DENSE DEPTH ACQUISITION VIA ONE-SHOT STRIPE STRUCTURED LIGHT

引用

ieee international conference on visual communications and image processing (vcip)

作者： Li, Qin Li, Fu Shi, Guangming Qi, Fei Shi, Yuexin Gao, Shan Xidian Univ Sch Elect Engn Key Lab Intelligent Percept & Image Understanding Chinese Minist Educ Xian 710071 Shaanxi Peoples R China

ISBN: (纸本)9781479902880

Depth acquisition for moving objects becomes increasingly critical for some applications such as human facial expression recognition. This paper presents a method for capturing the depth maps of moving objects that uses a one-shot black-and-white stripe pattern with the features of simplicity and easily generation. Considering the accuracy of a matching is crucial for a precise depth map but the matching of variant-width stripes is sparse and rough, the phase differences extracted by Gabor filter to achieve a pixel-wise matching with sub-pixel accuracy are used. The details of the derivation are presented to prove that this method based on the phase difference calculated by Gabor filter is valid. In addition, the periodic ambiguity of the encoded stripe is eliminated by the epipolar segment covering a given depth range at a camera-projector calibrating stage to decrease the calculation complexity. Experimental results show that our method can get a dense and accurate depth map of a moving object.

关键词： Structured light stripe pattern phase-difference based matching

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Retina Model Inspired image Quality Assessment

Retina Model Inspired Image Quality Assessment

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ieee international conference on visual communications and image processing (vcip)

作者： Zhai, Guangtao Kaup, Andre Wang, Jia Yang, Xiaokang Shanghai Jiao Tong Univ Inst Image Comm & Infor Proc Shanghai 200240 Peoples R China Univ Erlangen Nurnberg Chair Multimedia Commun & Signal Proc D-91058 Erlangen Germany

ISBN: (纸本)9781479902880

We proposed in this paper a retina model based approach for image quality assessment. The retinal model is consisted of an optical modulation transfer module and an adaptive low-pass filtering module. We treat the model as a black box and design the adaptive filer using an information theoretical approach. Since the information rate of visual signals is far beyond the processing power of the human visual system, there must be an effective data reduction stage in human visual brain. Therefore, the underlying assumption for the retina model is that the retina reduces the data amount of the visual scene while retaining as much useful information as possible. For full reference image quality assessment, the original and distorted images pass through the retinal filter before some kind of distance is calculated between the images. Retina filtering can serve as a general preprocessing stage for most existing image quality metrics. We show in this paper that retina model based MSE/PSNR, though being straightforward, has already state of the art performance on several image quality databases.

关键词： image Quality assessment Human visual System Retinal Model Mean Squared Error Peak Signal to Noise Ratio

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High-Fidelity Free-View Talking Head Synthesis for Low-Bandwidth Video conference

High-Fidelity Free-View Talking Head Synthesis for Low-Bandw...

引用

2023 ieee international conference on visual communications and image processing, vcip 2023

作者： Zhang, Zhiyu Tang, Anni Zhu, Chen Lu, Guo Xie, Rong Song, Li Shanghai Jiao Tong University Institute of Image Communication and Network Engineering Shanghai China

ISBN: (纸本)9798350359855

As video conferencing becomes an indispensable part of human's daliy life, how to achieve a high-fidelity calling experience under low bandwidth has been a popular and challenging issue. Deep generative models have great potential in low-bandwidth facial video compression due to the excellent generation capability based on abridged information. Nevertheless, exsiting deep generation-based compression methods tend to handle motion information in pure 2D or pseudo 3D space, causing facial distortion when large head poses are encountered. In this paper, we propose a 3D-aware high-fidelity facial video conferencing system based on a parameterized NeRF-based face model. Through the compression of the parameterized face model and the transmisstion of extracted facial parameters, we implement high-fidelity talking head synthesis for video conferencing at an ultra-low bitrate. Additionally, the 3D perception capability of the system allows for viewpoint control over the head, achieving higher interactivity and practicability. Extensive experiments verify the effectiveness of the proposed 3D-aware high-fidelity free-view facial video conferencing system. © 2023 ieee.

关键词： Video conferencing

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ALICE: Adapt your Learnable image Compression modEl for variable bitrates

ALICE: Adapt your Learnable Image Compression modEl for vari...

引用

2024 conference on visual communications and image processing

作者： Spadaro, Gabriele Ali, Muhammad Salman Presta, Alberto Pilo, Giommaria Bae, Sung-Ho Giraldo, Jhony H. Fiandrotti, Attilio Grangetto, Marco Tartaglione, Enzo Inst Polytech Paris Telecom Paris LTCI Paris France Univ Turin Turin Italy Kyung Hee Univ Yongin South Korea

ISBN: (纸本)9798331529543;9798331529550

When training a Learned image Compression model, the loss function is minimized such that the encoder and the decoder attain a target Rate-Distorsion trade-off. Therefore, a distinct model shall be trained and stored at the transmitter and receiver for each target rate, fostering the quest for efficient variable bitrate compression schemes. This paper proposes plugging Low-Rank Adapters into a transformer-based pre-trained LIC model and training them to meet different target rates. With our method, encoding an image at a variable rate is as simple as training the corresponding adapters and plugging them into the frozen pre-trained model. Our experiments show performance comparable with state-of-the-art fixed-rate LIC models at a fraction of the training and deployment cost. We publicly released the code at https://***/EIDOSLAB/ALICE.

关键词： image compression

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SINGLE image SUPER-RESOLUTION VIA PHASE CONGRUENCY ANALYSIS

SINGLE IMAGE SUPER-RESOLUTION VIA PHASE CONGRUENCY ANALYSIS

引用

ieee international conference on visual communications and image processing (vcip)

作者： Yu, Licheng Xu, Yi Zhang, Bo Shanghai Jiao Tong Univ Dept Elect Engn Shanghai Key Lab Digital Media Proc & Commun Shanghai 200240 Peoples R China

ISBN: (纸本)9781479902880

Single image super-resolution (SR) is a severely unconstrained task. While the self-example-based methods are able to reproduce sharp edges, they perform poorly for textures. For recovering the fine details, higher-level image segmentation and corresponding external texture database are employed in the example-based SR methods, but they involve too much human interaction. In this paper, we discuss the existing problems of example-based technique using scale space analysis. Accordingly, a robust pixel classification method is designed based on the phase congruency model in scale space, which can effectively divide images into edges, textures and flat regions. Then a super-resolution framework is proposed, which can adaptively emphasize the importance of high-frequency residuals in structural examples and scale invariant fractal property in textural regions. Experimental results show that our SR approach is able to present both sharp edges and vivid textures with few artifacts.

关键词： Phase congruency quaternion Gabor super-resolution example-based synthesis fractal-based enhancement

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Analysis of Smoothed LHE Methods for processing images with Optical Illusions 33

Analysis of Smoothed LHE Methods for Processing Images with ...

引用

33rd ieee international conference on visual communications and image processing (ieee vcip)

作者： Ambalathankandy, Prasoon Shimada, Takeshi Takamaeda, Shinya Motomura, Masato Asai, Tetsuya Ikebe, Masayuki Hokkaido Univ Res Ctr Integrated Quantum Elect Sapporo Hokkaido Japan Hokkaido Univ Grad Sch Informat Sci & Technol Sapporo Hokkaido Japan

ISBN: (纸本)9781538644584

To replicate human visual perception, we analyze processing images with optical illusion using edge preserving filters and smoothed local histogram equalization (LHE). images with the optical illusions are good models for gradual/rapid changes in contrast and strong edges, which are good cases for assessing the robustness of image filters. Here, we study and analyze the performance of smoothed LHE filters while processing perceptual illusion. Our studies conclude that, smoothed LHEs are useful in retaining actual edge forms in these images as they can operate using large kernel sizes. These large kernel size filters can construct sawtooth like edge and it corresponds to adequately wide halos. We also demonstrate the usefulness of smoothed LHE like tone mapping techniques in preserving naturalness, and we confirmed it by performing subjective visual test.

关键词： Edge preserving filter lateral inhibition local histogram equalization local tonemap optical illusion visual perception

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FRIDAY: Mitigating Unintentional Facial Identity in Deepfake Detectors Guided by Facial Recognizers

FRIDAY: Mitigating Unintentional Facial Identity in Deepfake...

引用

2024 conference on visual communications and image processing

作者： Kim, Younghun Kwon, Myung-Joon Lee, Wonjun Kim, Changick Korea Adv Inst Sci & Technol Grad Sch Green Growth & Sustainabil Daejeon South Korea Korea Adv Inst Sci & Technol Sch Elect Engn Daejeon South Korea

ISBN: (纸本)9798331529543;9798331529550

Previous Deepfake detection methods perform well within their training domains, but their effectiveness diminishes significantly with new synthesis techniques. Recent studies have revealed that detection models make decision boundaries based on facial identity instead of synthetic artifacts, leading to poor cross-domain performance. To address this issue, we propose FRIDAY, a novel training method that attenuates facial identity utilizing a face recognizer. To be specific, we first train a face recognizer using the same backbone as the Deepfake detector. We then freeze the recognizer and use it during the detector's training to mitigate facial identity information. This is achieved by feeding input images into both the recognizer and the detector, then minimizing the similarity of their feature embeddings using our Facial Identity Attenuating loss. This process encourages the detector to produce embeddings distinct from the recognizer, effectively attenuating facial identity. Comprehensive experiments demonstrate that our approach significantly improves detection performance on both in-domain and cross-domain datasets.

关键词： Deepfake Detection Unintentional Facial Identity Face Recognition image Forensics

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SALIENCY DETECTION BY ADAPTIVE CLUSTERING

SALIENCY DETECTION BY ADAPTIVE CLUSTERING

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ieee international conference on visual communications and image processing (vcip)

作者： Cao, Hai Li, Shaozi Su, Songzhi Cheng, Yun Ji, Rongrong Xiamen Univ Dept Cognit Sci Xiamen Peoples R China Fujian Key Lab Brain Like Inteligent Syst Xiamen Peoples R China Shandong Univ Weihai Dept Comp Sci Weihai Peoples R China HumanitasUniv HumanitasSci & Technol Loudi Peoples R China

ISBN: (纸本)9781479902880

Saliency detection plays an important role in image segmentation, content-aware resizing and object recognition. Most approaches obtain promising performance recently, which is useful for the postprocessing. We propose a clustering-based method to detect refined regions with comparative performance For coarse-grained classification with unknown clusters number, an adaptive algorithm called f-means is developed in this paper. Pixels are clustered by f-means based on color and spatial features, and then the centroids are used to compute their saliency values. Experiments show that our algorithm generates more fine maps, which outperform the state-of-the-art approaches on MSRA dataset. Relying on the saliency map, we also get superior results in foreground extracting, image resizing and thumbnails generation.

关键词： Saliency detection adaptive clustering visual attention image processing

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