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Learning to Fly with a Video Generator

Learning to Fly with a Video Generator

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Chia-Chun Chung Wen-Hsiao Peng Teng-Hu Cheng Chia-Hau Yu Natl Yang Ming Chiao Tung Univ Hsinchu Taiwan

ISBN: (纸本)9781728185514

This paper demonstrates a model-based reinforcement learning framework for training a self-flying drone. We implement the Dreamer proposed in a prior work as an environment model that responds to the action taken by the drone by predicting the next video frame as a new state signal. The Dreamer is a conditional video sequence generator. This model-based environment avoids the time-consuming interactions between the agent and the environment, speeding up largely the training process. This demonstration showcases for the first time the application of the Dreamer to train an agent that can finish the racing task in the Airsim simulator.

关键词： Training visual communication image processing Atmospheric modeling Video sequences Reinforcement learning Predictive models

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A study on Generative Adversarial Text to image Synthesis

A study on Generative Adversarial Text to Image Synthesis

引用

2023 International conference on Electrical, Computer, communications and Mechatronics Engineering, ICECCME 2023

作者： Tahmid, Marjana Alam, Samiul Akram, Kalim Asif Ashrafi, Kazi Muhammad East Delta University Dept. of Cse Chittagong Bangladesh East Delta University Dept. of Eee Chittagong Bangladesh Ulm University Dept. of Cse Ulm Germany

ISBN: (纸本)9798350322972

image captioning is one of the most prevalent and difficult challenges in Natural Language processing and Computer Vision: given an image, a written description of the image must be developed. The counterpart of the text to image problem is text to image synthesis, which involves creating a picture from a written description. These challenges approximate language translation challenges from a high-level perspective. images and text are two separate "languages"to convey related information, just like equivalent semantics might be represented in two different languages. This is undoubtedly beneficial, however existing AI systems are a long way from achieving this. Strong neural network topologies, such GANs (Generative Adversarial Networks), have been found to provide effective outcomes in recent years. There are, however, some text to image synthesis algorithms that use GAN (Generative Adversarial Network) that attempt to directly map words and characters to image pixels utilizing image synthesis and natural language synthesis approaches. To reconcile these advancements in text as well as image modeling and successfully translate visual representations from characters to pixels, we design an innovative deep architecture and GAN formulation in this study. Here, the demonstration of our model has been done by generating plausible images of birds and flowers from detailed text descriptions. © 2023 IEEE.

关键词： Generative adversarial networks

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3D Printing Design Simulation of Ceramic Products Based on 3D image Reproduction Technology 4th

3D Printing Design Simulation of Ceramic Products Based on 3...

引用

4th International conference on Machine Learning, image processing, Network Security and Data Sciences (MIND)

作者： Yao, Lan Shanghai Art & Design Acad Shanghai Peoples R China

ISBN: (纸本)9783031243660;9783031243677

With the development of communication technology, people will be exposed to more and more graphics and images in the process of life andwork. Like using digital devices such as camera, scanner and camera to obtain images, but these instruments and equipment can only obtain two-dimensional image information of objects, which is completely insufficient. Inmany fields, three-dimensional information of objects is necessary. In this paper, the 3D printing design of ceramic products is simulated based on 3D image reproduction technology. The satisfaction of users with the ceramic visual effect and hand-held comfort produced by 3D image reproduction simulation technology is investigated by means of questionnaire, and the computer vision technology and stereo matching technology are compared. The results show that more than 85% of users are very satisfied with the ceramic visual effect and hand-held comfort of three-dimensional image reproduction simulation technology, and less than 5% of users are not satisfied;The satisfaction of ceramic visual effect produced by computer vision technology and stereo matching technology is less than 60%, and the hand-held comfort is less than 70%.

关键词： 3D image reproduction technology Ceramic products 3D printing design Simulation research

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Scalable Privacy in Multi-Task image Compression

Scalable Privacy in Multi-Task Image Compression

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Alvar, Saeed Ranjbar Bajic, Ivan, V Simon Fraser Univ Sch Engn Sci Burnaby BC V5A 1S6 Canada

ISBN: (纸本)9781728185514

Learning-based compression systems have shown great potential for multi-task inference from their latent-space representation of the input image. In such systems, the decoder is supposed to be able to perform various analyses of the input image, such as object detection or segmentation, besides decoding the image. At the same time, privacy concerns around visual analytics have grown in response to the increasing capabilities of such systems to reveal private information. In this paper, we propose a method to make latent-space inference more privacy-friendly using mutual information-based criteria. In particular, we show how organizing and compressing the latent representation of the image according to task-specific mutual information can make the model maintain high analytics accuracy while becoming less able to reconstruct the input image and thereby reveal private information.

关键词： Learning-based compression privacy mutual information

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RDPlot - An Evaluation Tool for Video Coding Simulations

RDPlot - An Evaluation Tool for Video Coding Simulations

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Schneider, Jens Sauer, Johannes Wien, Mathias Rhein Westfal TH Aachen Inst Nachrichtentech Aachen Germany Rhein Westfal TH Aachen Lehrstuhl Bildverarbeitung Aachen Germany

ISBN: (纸本)9781728185514

RDPlot is an open source GUI application for plotting Rate-Distortion (RD)-curves and calculating Bjontegaard Delta (BD) statistics [1]. It supports parsing the output of commonly used reference software packages, parsing ∗.csv-formatted files, and ∗.xml-formatted files. Once parsed, RDPlot offers the ability to evaluate video coding results interactively. Conceptually, several measures can be plotted over the bitrate and BD measurements can be conducted accordingly. Moreover, plots and corresponding BD statistics can be exported, and directly integrated into LaTeX documents. © 2021 IEEE.

关键词： image coding

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Research on Vehicle Parking Aid System Based on Parking image Enhancement 10th

Research on Vehicle Parking Aid System Based on Parking Imag...

引用

10th International conference on communications, Signal processing, and Systems

作者： Ye, Danxian Yin, Xin Dong, Menghan Tianjin Normal Univ Tianjin Key Lab Wireless Mobile Commun & Power Tr Tianjin 300387 Peoples R China

ISBN: (纸本)9789811903908;9789811903892

At present, the visual parking assistance system in intelligent driving generally has the problems of unclear parking image quality and high hardware cost. In order to reduce the difficulty of parking and improve the ability to adapt to the environment, this paper proposes a vehicle assistance system based on parking image enhancement. Firstly, Retinex algorithm is used to balance the image illumination information and enhance the color saturation, so that it can adapt to more complex environmental conditions;secondly, Ackerman steering theorem is used to draw the dynamic parking aid line, and the coordinate transformation technology is used to output it to the vehicle screen. The adaptability and effectiveness of the developed system are verified by the relevant experimental research.

关键词： image enhancement Retinex algorithm Parking system Intelligent driving

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Parallelized Context Modeling for Faster image Coding

Parallelized Context Modeling for Faster Image Coding

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Koyuncu, A. Burakhan Cui, Kai Boev, Atanas Steinbach, Eckehard Tech Univ Munich Chair Media Technol Munich Germany Huawei Munich Res Ctr Audiovideo Technol Lab Munich Germany

ISBN: (纸本)9781728185514

Learning-based image compression has reached the performance of classical methods such as BPG. One common approach is to use an autoencoder network to map the pixel information to a latent space and then approximate the symbol probabilities in that space with a context model. During inference, the learned context model provides symbol probabilities, which are used by the entropy encoder to obtain the bitstream. Currently, the most effective context models use autoregression, but autoregression results in a very high decoding complexity due to the serialized data processing. In this work, we propose a method to parallelize the autoregressive process used for image compression. In our experiments, we achieve a decoding speed that is over 8 times faster than the standard autoregressive context model almost without compression performance reduction.

关键词： image compression

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image Reconstruction and Recognition of Optical Flow Based on Local Feature Extraction Mechanism of visual Cortex 1

引用

Proceedings of the 4th International conference on Neural Computing for Advanced Applications, NCAA 2023

作者： Lin, Wanyan Yi, Hao Li, Xiumin College of Automation Chongqing University Chongqing400030 China

ISBN: (数字)9789819958443

ISBN: (纸本)9789819958436

Neurons in the medial superior temporal (MSTd) region of the visual cortex of the brain can efficiently recognize the firing patterns from the neurons in the MT region. The process is similar to sparse coding in non-negative matrix decomposition (NMF), and the modular recognition of images can be achieved through synaptic plasticity learning rules. In this paper, a spiking neural network model based on spike-timing-dependent plasticity (STDP) is built to simulate the processing process of the visual cortex region MT-MSTD. Our results show that STDP can perform similar functions as NMF, i.e. generating sparse and linear superimposed output based on local features, so as to accurately reconstruct input stimuli for image reconstruction. Finally, support vector machine is used to achieve image recognition of optical flow inputs in eight directions. Compared with NMF, local feature extraction using STDP does not need to retrain the decision layer during the testing procedure of new optical flow samples, contributing to more efficient recognition of optical flow images. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Neurons

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A Deep Learning-based Audio-in-image Watermarking Scheme

A Deep Learning-based Audio-in-Image Watermarking Scheme

引用

IEEE International conference on visual communications and image processing (VCIP) - visual communications in the Era of AI and Limited Resources

作者： Das, Arjon Zhong, Xin Univ Nebraska Omaha Dept Comp Sci Omaha NE 68182 USA

ISBN: (纸本)9781728185514

This paper presents a deep learning-based audio-in-image watermarking scheme. Audio-in-image watermarking is the process of covertly embedding and extracting audio watermarks on a cover-image. Using audio watermarks can open up possibilities for different downstream applications. For the purpose of implementing an audio-in-image watermarking that adapts to the demands of increasingly diverse situations, a neural network architecture is designed to automatically learn the watermarking process in an unsupervised manner. In addition, a similarity network is developed to recognize the audio watermarks under distortions, therefore providing robustness to the proposed method. Experimental results have shown high fidelity and robustness of the proposed blind audio-in-image watermarking scheme.

关键词： Audio-in-image watermarking deep learning neural networks robustness

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Prompt-Based Segmentation and Inpainting : A New Approach to Disaster image Creation 14

Prompt-Based Segmentation and Inpainting : A New Approach to...

引用

14th International conference on Information and Communication Technology Convergence, ICTC 2023

作者： Choi, Minji Choi, Ji Hoon Won, Ru-Bin Bae, Byungjun University of Science and Technology Korea Information and Communication Engineering Daejeon Korea Republic of Media Intellectualization Research Lab Daejeon Korea Republic of

ISBN: (纸本)9798350313277

This paper proposes a novel approach to disaster image generation using prompt-based segmentation techniques. By segmenting terrains based on the provided prompt and inputting disaster-related prompts into the segmented area, we explore a method to generate images that reflect disaster scenarios. Moreover, we propose a method to adjust the inpainting mask area according to the severity of the disaster, providing a visual representation that varies with the situation. We acknowledge limitations in areas such as the inpainting mask region and the overall disaster image generation, and suggest directions for further research to overcome these challenges. We emphasize that the methodology of our study contributes significantly to disaster management and information dissemination. © 2023 IEEE.

关键词： disaster alert disaster image image inpainting image processing image segmentation text to image model

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