Search Results - "IEEE Conference on Computer Vision and Pattern Recognition. Proceedings"

Beyond short snippets: Deep networks for video classification by Ng, Joe Yue-Hei, Hausknecht, Matthew, Vijayanarasimhan, Sudheendra, Vinyals, Oriol, Monga, Rajat, Toderici, George

“…Convolutional neural networks (CNNs) have been extensively applied for image recognition problems giving state-of-the-art results on recognition, detection,…”
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Deeply learned face representations are sparse, selective, and robust by Sun, Yi, Wang, Xiaogang, Tang, Xiaoou

“…This paper designs a high-performance deep convolutional network (DeepID2+) for face recognition. It is learned with the identification-verification…”
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Deep filter banks for texture recognition and segmentation by Cimpoi, Mircea, Maji, Subhransu, Vedaldi, Andrea

“…Research in texture recognition often concentrates on the problem of material recognition in uncluttered conditions, an assumption rarely met by applications…”
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DeepID-Net: Deformable deep convolutional neural networks for object detection by Ouyang, Wanli, Wang, Xiaogang, Zeng, Xingyu, Qiu, Shi, Luo, Ping, Tian, Yonglong, Li, Hongsheng, Yang, Shuo, Wang, Zhe, Loy, Chen-Change, Tang, Xiaoou

“…In this paper, we propose deformable deep convolutional neural networks for generic object detection. This new deep learning object detection framework has…”
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Deformable part models are convolutional neural networks by Girshick, Ross, Iandola, Forrest, Darrell, Trevor, Malik, Jitendra

“…Deformable part models (DPMs) and convolutional neural networks (CNNs) are two widely used tools for visual recognition. They are typically viewed as distinct…”
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Filtered channel features for pedestrian detection by Zhang, Shanshan, Benenson, Rodrigo, Schiele, Bernt

“…This paper starts from the observation that multiple top performing pedestrian detectors can be modelled by using an intermediate layer filtering low-level…”
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Data-driven 3D Voxel Patterns for object category recognition by Yu Xiang, Wongun Choi, Yuanqing Lin, Savarese, Silvio

“…Despite the great progress achieved in recognizing objects as 2D bounding boxes in images, it is still very challenging to detect occluded objects and estimate…”
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100+ Times Faster Weighted Median Filter (WMF) by Zhang, Qi, Xu, Li, Jia, Jiaya

“…Weighted median, in the form of either solver or filter, has been employed in a wide range of computer vision solutions for its beneficial properties in…”
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Simultaneous video defogging and stereo reconstruction by Li, Zhuwen, Tan, Ping, Tan, Robby T., Zou, Danping, Zhou, Steven Zhiying, Cheong, Loong-Fah

“…We present a method to jointly estimate scene depth and recover the clear latent image from a foggy video sequence. In our formulation, the depth cues from…”
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Verifying liveness by multiple experts in face biometrics by Kollreider, K., Fronthaler, H., Bigun, J.

“…Resisting spoofing attempts via photographs and video playbacks is a vital issue for the success of face biometrics. Yet, the ldquolivenessrdquo topic has only…”
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Going deeper with convolutions by Szegedy, Christian, Wei Liu, Yangqing Jia, Sermanet, Pierre, Reed, Scott, Anguelov, Dragomir, Erhan, Dumitru, Vanhoucke, Vincent, Rabinovich, Andrew

“…We propose a deep convolutional neural network architecture codenamed Inception that achieves the new state of the art for classification and detection in the…”
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Fully convolutional networks for semantic segmentation by Long, Jonathan, Shelhamer, Evan, Darrell, Trevor

“…Convolutional networks are powerful visual models that yield hierarchies of features. We show that convolutional networks by themselves, trained end-to-end,…”
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FaceNet: A unified embedding for face recognition and clustering by Schroff, Florian, Kalenichenko, Dmitry, Philbin, James

“…Despite significant recent advances in the field of face recognition [10, 14, 15, 17], implementing face verification and recognition efficiently at scale…”
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3D ShapeNets: A deep representation for volumetric shapes by Zhirong Wu, Song, Shuran, Khosla, Aditya, Fisher Yu, Linguang Zhang, Xiaoou Tang, Xiao, Jianxiong

“…3D shape is a crucial but heavily underutilized cue in today's computer vision systems, mostly due to the lack of a good generic shape representation. With the…”
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Show and tell: A neural image caption generator by Vinyals, Oriol, Toshev, Alexander, Bengio, Samy, Erhan, Dumitru

“…Automatically describing the content of an image is a fundamental problem in artificial intelligence that connects computer vision and natural language…”
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CIDEr: Consensus-based image description evaluation by Vedantam, Ramakrishna, Zitnick, C. Lawrence, Parikh, Devi

“…Automatically describing an image with a sentence is a long-standing challenge in computer vision and natural language processing. Due to recent progress in…”
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Deep visual-semantic alignments for generating image descriptions by Karpathy, Andrej, Fei-Fei, Li

“…We present a model that generates natural language descriptions of images and their regions. Our approach leverages datasets of images and their sentence…”
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Long-term recurrent convolutional networks for visual recognition and description by Donahue, Jeff, Hendricks, Lisa Anne, Guadarrama, Sergio, Rohrbach, Marcus, Venugopalan, Subhashini, Darrell, Trevor, Saenko, Kate

“…Models based on deep convolutional networks have dominated recent image interpretation tasks; we investigate whether models which are also recurrent, or…”
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Delving into egocentric actions by Yin Li, Zhefan Ye, Rehg, James M.

“…We address the challenging problem of recognizing the camera wearer's actions from videos captured by an egocentric camera. Egocentric videos encode a rich set…”
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ActivityNet: A large-scale video benchmark for human activity understanding by Caba Heilbron, Fabian, Escorcia, Victor, Ghanem, Bernard, Niebles, Juan Carlos

“…In spite of many dataset efforts for human action recognition, current computer vision algorithms are still severely limited in terms of the variability and…”
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