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检索条件"任意字段=IEEE Conference on Computer Vision and Pattern Recognition Workshops"

共 23198 条记录，以下是261-270 订阅

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Fast Solvers for Minimal Radial Distortion Relative Pose Problems

Fast Solvers for Minimal Radial Distortion Relative Pose Pro...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Oskarsson, Magnus Lund Univ Ctr Math Sci Lund Sweden

ISBN: (纸本)9781665448994

In this paper we present a unified formulation for a large class of relative pose problems with radial distortion and varying calibration. For minimal cases, we show that one can eliminate the number of parameters down to one to three. The relative pose can then be expressed using varying calibration constraints on the fundamental matrix, with entries that are polynomial in the parameters. We can then apply standard techniques based on the action matrix and Sturm sequences to construct our solvers. This enables efficient solvers for a large class of relative pose problems with radial distortion, using a common framework. We evaluate a number of these solvers for robust two-view inlier and epipolar geometry estimation, used as minimal solvers in RANSAC.

关键词： Geometry computer vision conferences Estimation Tools Distortion Cameras

来源：评论

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Rethinking Supervised Depth Estimation for 360° Panoramic Imagery

Rethinking Supervised Depth Estimation for 360° Panoramic I...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： He, Lu Jian, Bing Wen, Yangming Zhu, Haichao Liu, Kelin Feng, Weiwei Liu, Shan Tencent Amer Palo Alto CA 94306 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

Depth estimation from a single 360 degrees panorama image is a difficult task. It is an ill-posed problem to estimate depth maps from an RGB panorama image due to the intrinsic scale ambiguity issue. To mitigate the scale inconsistency issue in the ground truth depth map, we propose a simple yet effective method to normalize the depth data based on estimated camera height. In addition, we design a multiple head planar-guided depth network, to provide more geometric constraints for depth estimation. Experimental results show that our relative depth estimation task is more accurate than the absolute depth estimation task, and our proposed model produces state-of-the-art performance on both Matterport3D and Stanford2D3D datasets.

关键词： Measurement computer vision Head conferences Estimation Data models pattern recognition

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Neurodata Lab's approach to the Challenge on computer vision for Physiological Measurement

Neurodata Lab's approach to the Challenge on Computer Vision...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Artemyev, Mikhail Churikova, Marina Grinenko, Mikhail Perepelkina, Olga Neurodata Lab LLC Miami FL 33137 USA Lomonosov Moscow State Univ Fac Biol Dept Higher Nervous Act Moscow Russia

ISBN: (纸本)9781728193601

This paper introduces the Neurodata Lab's approach presented at the 1st Challenge on Remote Physiological Signal Sensing (RePSS) organized within CVPR2020. The RePSS challenge was focused on measuring the average heart rate from color facial videos, which is one of the most fundamental problems in the field of computer vision. Our deep learning-based approach includes 3D spatio-temporal attention convolutional neural network for photoplethysmogram extraction and 1D convolutional neural network pre-trained on synthetic data for time series analysis. It provides state-of-the-art results outperforming those of other participants on a mixture of VIPL and OBF databases: MAE=6.94 (12.3% improvement compared to the top-2 result), RMSE=10.68 (24.6% improvement), Pearson R = 0.755 (28.2% improvement).

关键词： computer vision

来源：评论

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Connecting NeRFs, Images, and Text

Connecting NeRFs, Images, and Text

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Ballerini, Francesco Ramirez, Pierluigi Zama Mirabella, Roberto Salti, Samuele Di Stefano, Luigi Univ Bologna Bologna Italy

ISBN: (纸本)9798350365474

Neural Radiance Fields (NeRFs) have emerged as a standard framework for representing 3D scenes and objects, introducing a novel data type for information exchange and storage. Concurrently, significant progress has been made in multimodal representation learning for text and image data. This paper explores a novel research direction that aims to connect the NeRF modality with other modalities, similar to established methodologies for images and text. To this end, we propose a simple framework that exploits pre-trained models for NeRF representations alongside multimodal models for text and image processing. Our framework learns a bidirectional mapping between NeRF embeddings and those obtained from corresponding images and text. This mapping unlocks several novel and useful applications, including NeRF zero-shot classification and NeRF retrieval from images or text.

关键词： 3D computer vision Neural Fields

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vision on Wheels: Looking at Driver, Vehicle, and Surround for On-Road Maneuver Analysis

Vision on Wheels: Looking at Driver, Vehicle, and Surround f...

引用

27th ieee conference on computer vision and pattern recognition (CVPR)

作者： Ohn-Bar, Eshed Tawari, Ashish Martin, Sujitha Trivedi, Mohan M. Univ Calif San Diego Comp Vis & Robot Res Lab San Diego CA 92103 USA

ISBN: (纸本)9781479943098

Automotive systems provide a unique opportunity for mobile vision technologies to improve road safety by understanding and monitoring the driver. In this work, we propose a real-time framework for early detection of driver maneuvers. The implications of this study would allow for better behavior prediction, and therefore the development of more efficient advanced driver assistance and warning systems. Cues are extracted from an array of sensors observing the driver (head, hand, and foot), the environment (lane and surrounding vehicles), and the ego-vehicle state (speed, steering angle, etc.). Evaluation is performed on a real-world dataset with overtaking maneuvers, showing promising results. In order to gain better insight into the processes that characterize driver behavior, temporally discriminative cues are studied and visualized.

关键词： active safety driver assistance systems mobile vision applications real-time behavior analysis temporal action recognition

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WiCV 2018: The Fourth Women In computer vision Workshop 31

WiCV 2018: The Fourth Women In Computer Vision Workshop

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Demir, Ilke Bazazian, Dena Romero, Adriana Sharmanska, Viktoriia Tchapmi, Lyne P. Facebook Menlo Pk CA 94025 USA Comp Vis Ctr Barcelona Spain Facebook AI Res Montreal PQ Canada Imperial Coll London London England Stanford Univ Stanford CA 94305 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

We present WiCV 2018 - Women in computer vision Workshop to increase the visibility and inclusion of women researchers in computer vision field, organized in conjunction with CVPR 2018. computer vision and machine learning have made incredible progress over the past years, yet the number of female researchers is still low both in academia and industry. WiCV is organized to raise visibility of female researchers, to increase the collaboration, and to provide mentorship and give opportunities to female-identifying junior researchers in the field. In its fourth year, we are proud to present the changes and improvements over the past years, summary of statistics for presenters and attendees, followed by expectations from future generations.

关键词： conferences computer vision Industries Object recognition Engineering profession Collaboration Machine learning

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Fixation and Saccade based Face recognition from Single Image per Person with Various Occlusions and Expressions

Fixation and Saccade based Face Recognition from Single Imag...

引用

26th ieee conference on computer vision and pattern recognition (CVPR)

作者： Wei, Xingjie Li, Chang-Tsun Univ Warwick Dept Comp Sci Coventry CV4 7AL W Midlands England

ISBN: (纸本)9780769549903

Face recognition technique is widely used in the real-world applications over the past decade. Different from other biometric traits such as fingerprint and iris, face is the biological nature for humans to recognise a person even met just once. In this paper, we propose a novel method, which simulates the mechanism of fixations and saccades in human visual perception, to handle the face recognition from single image per person problem. Our method is robust to the local deformations of the face (i.e., expression changes and occlusions). Especially for the occlusion related problems, which have not received enough attentions compared with other challenging variations of illumination, expression and pose, our method significantly outperforms the state-of-the-art approaches despite various types of occlusions. Experimental results on the FRGC and the AR databases confirm the effectiveness of our method.

关键词： computer graphics face recognition

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End-to-end Optimized Video Compression with MV-Residual Prediction

End-to-end Optimized Video Compression with MV-Residual Pred...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Wu, XiangJi Zhang, Ziwen Feng, Jie Zhou, Lei Wu, Junmin Tucodec Inc Shanghai Peoples R China

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193601

We present an end-to-end trainable framework for P-frame compression in this paper. A joint motion vector (MV) and residual prediction network MV-Residual is designed to extract the ensembled features of motion representations and residual information by treating the two successive frames as inputs. The prior probability of the latent representations is modeled by a hyperprior auto-encoder and trained jointly with the MV-Residual network. Specially, the spatially-displaced convolution is applied for video frame prediction, in which a motion kernel for each pixel is learned to generate predicted pixel by applying the kernel at a displaced location in the source image. Finally, novel rate allocation and post-processing strategies are used to produce the final compressed bits, considering the bits constraint of the challenge. The experimental results on validation set show that the proposed optimized framework can generate the highest MS-SSIM for P-frame compression competition.

关键词： Image coding Video compression Convolution Kernel computer vision conferences pattern recognition

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Active vision Dataset Benchmark 31

Active Vision Dataset Benchmark

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Ammirato, Phil Berg, Alexander C. Kosecka, Jana Univ N Carolina Chapel Hill NC 27514 USA George Mason Univ Fairfax VA 22030 USA

ISBN: (数字)9781538661000

ISBN: (纸本)9781538661000

Several recent efforts in computer vision indicate a trend toward studying and understanding problems in larger scale environments, beyond single images, and focus on connections to tasks in navigation, mobile manipulation, and visual question answering. A common goal of these tasks is the capability of moving in the environment, acquiring novel views during perception and while performing a task. This capability comes easily in synthetic environments, however achieving the same effect with real images is much more laborious. We propose using the existing Active vision Dataset to form a benchmark for such problems in a real-world settings with real images. The dataset is well suited for evaluating tasks of multiview active recognition, target driven navigation, and target search, and also can be effective for studying the transfer of strategies learned in simulation to real settings.

关键词： Task analysis Training Visualization Robots Benchmark testing Navigation

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Evaluating the Immediate Applicability of Pose Estimation for Sign Language recognition

Evaluating the Immediate Applicability of Pose Estimation fo...

引用

ieee/CVF conference on computer vision and pattern recognition (CVPR)

作者： Moryossef, Amit Tsochantaridis, Ioannis Dinn, Joe Camgoez, Necati Cihan Bowden, Richard Jiang, Tao Rios, Annette Muller, Mathias Ebling, Sarah Bar Ilan Univ Ramat Gan Israel Google Mountain View CA 94043 USA Univ Surrey Guildford Surrey England Univ Zurich Zurich Switzerland

ISBN: (纸本)9781665448994

Sign languages are visual languages produced by the movement of the hands, face, and body. In this paper, we evaluate representations based on skeleton poses, as these are explainable, person-independent, privacy-preserving, low-dimensional representations. Basically, skeletal representations generalize over an individual's appearance and background, allowing us to focus on the recognition of motion. But how much information is lost by the skeletal representation? We perform two independent studies using two state-of-the-art pose estimation systems. We analyze the applicability of the pose estimation systems to sign language recognition by evaluating the failure cases of the recognition models. Importantly, this allows us to characterize the current limitations of skeletal pose estimation approaches in sign language recognition.

关键词： Analytical models Visualization computer vision Assistive technology Face recognition conferences Pose estimation

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