Search Results - "2022 IEEE International Conference on Image Processing (ICIP)"

Slicing Aided Hyper Inference and Fine-Tuning for Small Object Detection by Akyon, Fatih Cagatay, Onur Altinuc, Sinan, Temizel, Alptekin

“…Detection of small objects and objects far away in the scene is a major challenge in surveillance applications. Such objects are represented by small number of…”
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6d Rotation Representation For Unconstrained Head Pose Estimation by Hempel, Thorsten, Abdelrahman, Ahmed A., Al-Hamadi, Ayoub

“…In this paper, we present a method for unconstrained end-to-end head pose estimation. We address the problem of ambiguous rotation labels by introducing the…”
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Image Fusion Transformer by Vs, Vibashan, Jose Valanarasu, Jeya Maria, Oza, Poojan, Patel, Vishal M.

“…In image fusion, images obtained from different sensors are fused to generate a single image with enhanced information. In recent years, state-of-the-art…”
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Reviving Iterative Training with Mask Guidance for Interactive Segmentation by Sofiiuk, Konstantin, Petrov, Ilya A., Konushin, Anton

“…Recent works on click-based interactive segmentation have demonstrated state-of-the-art results by using various inference-time optimization schemes. These…”
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Anomalib: A Deep Learning Library for Anomaly Detection by Akcay, Samet, Ameln, Dick, Vaidya, Ashwin, Lakshmanan, Barath, Ahuja, Nilesh, Genc, Utku

“…This paper introduces anomalib 1 , a novel library for unsupervised anomaly detection and localization. With reproducibility and modularity in mind, this…”
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Exploiting Spatial Sparsity for Event Cameras with Visual Transformers by Wang, Zuowen, Hu, Yuhuang, Liu, Shih-Chii

“…Event cameras report local changes of brightness through an asynchronous stream of output events. Events are spatially sparse at pixel locations with little…”
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Joint Motion Correction and 3D Segmentation with Graph-Assisted Neural Networks for Retinal OCT by Wang, Yiqian, Galang, Carlo, Freeman, William R., Nguyen, Truong Q., An, Cheolhong

“…Optical Coherence Tomography (OCT) is a widely used noninvasive high resolution 3D imaging technique for biological tissues and plays an important role in…”
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Unsupervised Video Segmentation Algorithms Based On Flexibly Regularized Mixture Models by Launay, Claire, Vacher, Jonathan, Coen-Cagli, Ruben

“…We propose a family of probabilistic segmentation algorithms for videos that rely on a generative model capturing static and dynamic natural image statistics…”
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Depthformer: Multiscale Vision Transformer for Monocular Depth Estimation with Global Local Information Fusion by Agarwal, Ashutosh, Arora, Chetan

“…Attention-based models such as transformers have shown outstanding performance on dense prediction tasks, such as semantic segmentation, owing to their…”
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CMA-CLIP: Cross-Modality Attention Clip for Text-Image Classification by Fu, Jinmiao, Xu, Shaoyuan, Liu, Huidong, Liu, Yang, Xie, Ning, Wang, Chien-Chih, Liu, Jia, Sun, Yi, Wang, Bryan

“…Multi-modal learning with both text and images benefits multiple applications, such as attribute extraction for e-commerce products. In this paper, we propose…”
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Deep Active Learning for Cryo-Electron Tomography Classification by Wang, Tianyang, Li, Bo, Zhang, Jing, Zeng, Xiangrui, Uddin, Mostofa Rafid, Wu, Wei, Xu, Min

“…Cryo-Electron Tomography (cryo-ET) is an emerging 3D imaging technique which shows great potentials in structural biology research. One of the main challenges…”
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One-Cycle Pruning: Pruning Convnets With Tight Training Budget by Hubens, Nathan, Mancas, Matei, Gosselin, Bernard, Preda, Marius, Zaharia, Titus

“…Introducing sparsity in a convnet has been an efficient way to reduce its complexity while keeping its performance almost intact. Most of the time, sparsity is…”
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Excavating RoI Attention for Underwater Object Detection by Liang, Xutao, Song, Pinhao

“…Self-attention is one of the most successful designs in deep learning, which calculates the similarity of different tokens and reconstructs the feature based…”
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The Hyperview Challenge: Estimating Soil Parameters from Hyperspectral Images by Nalepa, Jakub, Le Saux, Bertrand, Longepe, Nicolas, Tulczyjew, Lukasz, Myller, Michal, Kawulok, Michal, Smykala, Krzysztof, Gumiela, Michal

“…Improving agricultural practices through exploiting the recent imaging and machine learning advancements plays a key role nowadays to ensure sustainable food…”
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Efficient Inference Of Image-Based Neural Network Models In Reconfigurable Systems With Pruning And Quantization by Flich, Jose, Medina, Laura, Catalan, Izan, Hernandez, Carles, Bragagnolo, Andrea, Auzanneau, Fabrice, Briand, David

“…Neural networks (NN) for image processing in embedded systems expose two conflicting requirements: increasing computing power needs as models become more…”
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Unbiased Validation of the Algorithms for Automatic Needle Localization in Ultrasound-Guided Breast Biopsies by Wijata, Agata M., Nalepa, Jakub

“…Automatic localization of the biopsy needle in ultrasound images has become an important medical image analysis task, because it can directly translate to…”
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On The Link Between Emotion, Attention And Content In Virtual Immersive Environments by Guimard, Quentin, Robert, Florent, Bauce, Camille, Ducreux, Aldric, Sassatelli, Lucile, Wu, Hui-Yin, Winckler, Marco, Gros, Auriane

“…While immersive media have been shown to generate more intense emotions, saliency information has been shown to be a key component for the assessment of their…”
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Image Compression Based on Importance Using Optimal Mass Transportation Map by Li, Zihang, An, Dongsheng, Feng, Yingjie, Gu, Xianfeng, Xu, Xiaoyin, Zhang, Min

“…Demand for efficient image transmission and storage is in-creasing rapidly because of the continuing growth of multi-media technology and VR and AR…”
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Blind Quality of a 3D Reconstructed MESH by Alcouffe, Remy, Gasparini, Simone, Morin, Geraldine, Chambon, Sylvie

“…This paper proposes blind mesh quality measures for a reconstructed 3D model. The assessment of 3D model quality is a fundamental step in the process of 3D…”
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Fusioncount: Efficient Crowd Counting Via Multiscale Feature Fusion by Ma, Yiming, Sanchez, Victor, Guha, Tanaya

“…State-of-the-art crowd counting models follow an encoder-decoder approach. Images are first processed by the encoder to extract features. Then, to account for…”
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