Suchergebnisse - "2018 IEEE CVF Conference on Computer Vision and Pattern Recognition"

VizWiz Grand Challenge: Answering Visual Questions from Blind People von Gurari, Danna, Li, Qing, Stangl, Abigale J., Guo, Anhong, Lin, Chi, Grauman, Kristen, Luo, Jiebo, Bigham, Jeffrey P.

“… The study of algorithms to automatically answer visual questions currently is motivated by visual question answering (VQA) datasets constructed in artificial …”
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DenseASPP for Semantic Segmentation in Street Scenes von Yang, Maoke, Yu, Kun, Zhang, Chi, Li, Zhiwei, Yang, Kuiyuan

“… Semantic image segmentation is a basic street scene understanding task in autonomous driving, where each pixel in a high resolution image is categorized into a …”
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Single-Shot Refinement Neural Network for Object Detection von Zhang, Shifeng, Wen, Longyin, Bian, Xiao, Lei, Zhen, Li, Stan Z.

“… For object detection, the two-stage approach (e.g., Faster R-CNN) has been achieving the highest accuracy, whereas the one-stage approach (e.g., SSD) has the …”
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DensePose: Dense Human Pose Estimation in the Wild von Guler, Riza Alp, Neverova, Natalia, Kokkinos, Iasonas

“… In this work we establish dense correspondences between an RGB image and a surface-based representation of the human body, a task we refer to as dense human …”
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Real-Time Seamless Single Shot 6D Object Pose Prediction von Tekin, Bugra, Sinha, Sudipta N., Fua, Pascal

“… We propose a single-shot approach for simultaneously detecting an object in an RGB image and predicting its 6D pose without requiring multiple stages or having …”
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Mask-Guided Contrastive Attention Model for Person Re-identification von Song, Chunfeng, Huang, Yan, Ouyang, Wanli, Wang, Liang

“… Person Re-identification (ReID) is an important yet challenging task in computer vision. Due to the diverse background clutters, variations on viewpoints and …”
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Deformable GANs for Pose-Based Human Image Generation von Siarohin, Aliaksandr, Sangineto, Enver, Lathuiliere, Stephane, Sebe, Nicu

“… In this paper we address the problem of generating person images conditioned on a given pose. Specifically, given an image of a person and a target pose, we …”
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Features for Multi-target Multi-camera Tracking and Re-identification von Ristani, Ergys, Tomasi, Carlo

“… Multi-Target Multi-Camera Tracking (MTMCT) tracks many people through video taken from several cameras. Person Re-Identification (Re-ID) retrieves from a …”
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Unsupervised Cross-Dataset Person Re-identification by Transfer Learning of Spatial-Temporal Patterns von Lv, Jianming, Chen, Weihang, Li, Qing, Yang, Can

“… Most of the proposed person re-identification algorithms conduct supervised training and testing on single labeled datasets with small size, so directly …”
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Who's Better? Who's Best? Pairwise Deep Ranking for Skill Determination von Doughty, Hazel, Damen, Dima, Mayol-Cuevas, Walterio

“… This paper presents a method for assessing skill from video, applicable to a variety of tasks, ranging from surgery to drawing and rolling pizza dough. We …”
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Deep Ordinal Regression Network for Monocular Depth Estimation von Fu, Huan, Gong, Mingming, Wang, Chaohui, Batmanghelich, Kayhan, Tao, Dacheng

“… Monocular depth estimation, which plays a crucial role in understanding 3D scene geometry, is an ill-posed problem. Recent methods have gained significant …”
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Squeeze-and-Excitation Networks von Hu, Jie, Shen, Li, Sun, Gang

“… Convolutional neural networks are built upon the convolution operation, which extracts informative features by fusing spatial and channel-wise information …”
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MobileNetV2: Inverted Residuals and Linear Bottlenecks von Sandler, Mark, Howard, Andrew, Zhu, Menglong, Zhmoginov, Andrey, Chen, Liang-Chieh

“… In this paper we describe a new mobile architecture, MobileNetV2, that improves the state of the art performance of mobile models on multiple tasks and …”
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Non-local Neural Networks von Wang, Xiaolong, Girshick, Ross, Gupta, Abhinav, He, Kaiming

“… Both convolutional and recurrent operations are building blocks that process one local neighborhood at a time. In this paper, we present non-local operations …”
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ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices von Zhang, Xiangyu, Zhou, Xinyu, Lin, Mengxiao, Sun, Jian

“… We introduce an extremely computation-efficient CNN architecture named ShuffleNet, which is designed specially for mobile devices with very limited computing …”
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Cascade R-CNN: Delving Into High Quality Object Detection von Cai, Zhaowei, Vasconcelos, Nuno

“… In object detection, an intersection over union (IoU) threshold is required to define positives and negatives. An object detector, trained with low IoU …”
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High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANs von Wang, Ting-Chun, Liu, Ming-Yu, Zhu, Jun-Yan, Tao, Andrew, Kautz, Jan, Catanzaro, Bryan

“… We present a new method for synthesizing high-resolution photo-realistic images from semantic label maps using conditional generative adversarial networks …”
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StarGAN: Unified Generative Adversarial Networks for Multi-domain Image-to-Image Translation von Choi, Yunjey, Choi, Minje, Kim, Munyoung, Ha, Jung-Woo, Kim, Sunghun, Choo, Jaegul

“… Recent studies have shown remarkable success in image-to-image translation for two domains. However, existing approaches have limited scalability and …”
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Residual Dense Network for Image Super-Resolution von Zhang, Yulun, Tian, Yapeng, Kong, Yu, Zhong, Bineng, Fu, Yun

“… A very deep convolutional neural network (CNN) has recently achieved great success for image super-resolution (SR) and offered hierarchical features as well …”
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Boosting Adversarial Attacks with Momentum von Dong, Yinpeng, Liao, Fangzhou, Pang, Tianyu, Su, Hang, Zhu, Jun, Hu, Xiaolin, Li, Jianguo

“… Deep neural networks are vulnerable to adversarial examples, which poses security concerns on these algorithms due to the potentially severe consequences …”
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