Search Results - "Image Processing and Computer Vision"

Non-Local Image Inpainting Using Low-Rank Matrix Completion by Li, Wei, Zhao, Lei, Lin, Zhijie, Xu, Duanqing, Lu, Dongming

“…In this paper, we propose a highly accurate inpainting algorithm which reconstructs an image from a fraction of its pixels. Our algorithm is inspired by the…”
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Volumetric Data Reduction in a Compressed Sensing Framework by Xu, X., Sakhaee, E., Entezari, A.

“…In this paper, we investigate compressed sensing principles to devise an in‐situ data reduction framework for visualization of volumetric datasets. We exploit…”
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Fast High-Dimensional Filtering Using the Permutohedral Lattice by Adams, Andrew, Baek, Jongmin, Davis, Myers Abraham

“…Many useful algorithms for processing images and geometry fall under the general framework of high‐dimensional Gaussian filtering. This family of algorithms…”
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Shared Sampling for Real-Time Alpha Matting by Gastal, Eduardo S. L., Oliveira, Manuel M.

“…Image matting aims at extracting foreground elements from an image by means of color and opacity (alpha) estimation. While a lot of progress has been made in…”
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DRIT++: Diverse Image-to-Image Translation via Disentangled Representations by Lee, Hsin-Ying, Tseng, Hung-Yu, Mao, Qi, Huang, Jia-Bin, Lu, Yu-Ding, Singh, Maneesh, Yang, Ming-Hsuan

“…Image-to-image translation aims to learn the mapping between two visual domains. There are two main challenges for this task: (1) lack of aligned training…”
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Exploiting Diffusion Prior for Real-World Image Super-Resolution by Wang, Jianyi, Yue, Zongsheng, Zhou, Shangchen, Chan, Kelvin C. K., Loy, Chen Change

“…We present a novel approach to leverage prior knowledge encapsulated in pre-trained text-to-image diffusion models for blind super-resolution. Specifically, by…”
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The Open Images Dataset V4: Unified Image Classification, Object Detection, and Visual Relationship Detection at Scale by Kuznetsova, Alina, Rom, Hassan, Alldrin, Neil, Uijlings, Jasper, Krasin, Ivan, Pont-Tuset, Jordi, Kamali, Shahab, Popov, Stefan, Malloci, Matteo, Kolesnikov, Alexander, Duerig, Tom, Ferrari, Vittorio

“…We present Open Images V4, a dataset of 9.2M images with unified annotations for image classification, object detection and visual relationship detection. The…”
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Learning to Prompt for Vision-Language Models by Zhou, Kaiyang, Yang, Jingkang, Loy, Chen Change, Liu, Ziwei

“…Large pre-trained vision-language models like CLIP have shown great potential in learning representations that are transferable across a wide range of…”
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CLIP-Adapter: Better Vision-Language Models with Feature Adapters by Gao, Peng, Geng, Shijie, Zhang, Renrui, Ma, Teli, Fang, Rongyao, Zhang, Yongfeng, Li, Hongsheng, Qiao, Yu

“…Large-scale contrastive vision-language pretraining has shown significant progress in visual representation learning. Unlike traditional visual systems trained…”
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FairMOT: On the Fairness of Detection and Re-identification in Multiple Object Tracking by Zhang, Yifu, Wang, Chunyu, Wang, Xinggang, Zeng, Wenjun, Liu, Wenyu

“…Multi-object tracking (MOT) is an important problem in computer vision which has a wide range of applications. Formulating MOT as multi-task learning of object…”
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BiSeNet V2: Bilateral Network with Guided Aggregation for Real-Time Semantic Segmentation by Yu, Changqian, Gao, Changxin, Wang, Jingbo, Yu, Gang, Shen, Chunhua, Sang, Nong

“…Low-level details and high-level semantics are both essential to the semantic segmentation task. However, to speed up the model inference, current approaches…”
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Generalized Out-of-Distribution Detection: A Survey by Yang, Jingkang, Zhou, Kaiyang, Li, Yixuan, Liu, Ziwei

“…Out-of-distribution (OOD) detection is critical to ensuring the reliability and safety of machine learning systems. For instance, in autonomous driving, we…”
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Grad-CAM: Visual Explanations from Deep Networks via Gradient-Based Localization by Selvaraju, Ramprasaath R., Cogswell, Michael, Das, Abhishek, Vedantam, Ramakrishna, Parikh, Devi, Batra, Dhruv

“…We propose a technique for producing ‘visual explanations’ for decisions from a large class of Convolutional Neural Network (CNN)-based models, making them…”
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MFFN: image super-resolution via multi-level features fusion network by Chen, Yuantao, Xia, Runlong, Yang, Kai, Zou, Ke

“…Deep convolutional neural networks can effectively improve the performance of single-image super-resolution reconstruction. Deep networks tend to achieve…”
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Adding Depth to Cartoons Using Sparse Depth (In)equalities by Sýkora, D., Sedlacek, D., Jinchao, S., Dingliana, J., Collins, S.

“…This paper presents a novel interactive approach for adding depth information into hand‐drawn cartoon images and animations. In comparison to previous depth…”
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Rescaling Egocentric Vision: Collection, Pipeline and Challenges for EPIC-KITCHENS-100 by Damen, Dima, Doughty, Hazel, Farinella, Giovanni Maria, Furnari, Antonino, Kazakos, Evangelos, Ma, Jian, Moltisanti, Davide, Munro, Jonathan, Perrett, Toby, Price, Will, Wray, Michael

“…This paper introduces the pipeline to extend the largest dataset in egocentric vision, EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection…”
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Human Action Recognition and Prediction: A Survey by Kong, Yu, Fu, Yun

“…Derived from rapid advances in computer vision and machine learning, video analysis tasks have been moving from inferring the present state to predicting the…”
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HOTA: A Higher Order Metric for Evaluating Multi-object Tracking by Luiten, Jonathon, Os̆ep, Aljos̆a, Dendorfer, Patrick, Torr, Philip, Geiger, Andreas, Leal-Taixé, Laura, Leibe, Bastian

“…Multi-object tracking (MOT) has been notoriously difficult to evaluate. Previous metrics overemphasize the importance of either detection or association. To…”
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Deep Learning for Generic Object Detection: A Survey by Liu, Li, Ouyang, Wanli, Wang, Xiaogang, Fieguth, Paul, Chen, Jie, Liu, Xinwang, Pietikäinen, Matti

“…Object detection, one of the most fundamental and challenging problems in computer vision, seeks to locate object instances from a large number of predefined…”
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Pix2Vox++: Multi-scale Context-aware 3D Object Reconstruction from Single and Multiple Images by Xie, Haozhe, Yao, Hongxun, Zhang, Shengping, Zhou, Shangchen, Sun, Wenxiu

“…Recovering the 3D shape of an object from single or multiple images with deep neural networks has been attracting increasing attention in the past few years…”
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