ccvl.stat.ucla.edu

CCVL | Center for Cognition, Vision, and Learning – UCLA

Center for Cognition, Vision, and Learning. Prof Alan L. Yuille, UCLA. Pixelwise-annotated. 400 categories. On 20,000 images. Visual Cortex on Silicon. An NSF Expedition in Computing. Download our new datasets, pixel-wise manually annotated by trained students. Center for Brains, Minds and Machines. CCVL is affiliated to the Center for Brains, Minds and Machines, MIT. Visual Cortex on Silicon. CCVL is member of the NSF Expedition Project Visual Cortex on Silicon . Mathematical Sciences Building, Room 8125.

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CCVL | Center for Cognition, Vision, and Learning – UCLA | ccvl.stat.ucla.edu Reviews

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Center for Cognition, Vision, and Learning. Prof Alan L. Yuille, UCLA. Pixelwise-annotated. 400 categories. On 20,000 images. Visual Cortex on Silicon. An NSF Expedition in Computing. Download our new datasets, pixel-wise manually annotated by trained students. Center for Brains, Minds and Machines. CCVL is affiliated to the Center for Brains, Minds and Machines, MIT. Visual Cortex on Silicon. CCVL is member of the NSF Expedition Project Visual Cortex on Silicon . Mathematical Sciences Building, Room 8125.

<META> KEYWORDS

1 ccvl

2 datasets

3 deeplab models

4 deeplab weak em adapt

5 deeplab

6 deeplab coco largefov

7 deeplab coco strong

8 deeplab largefov

9 deeplab largefov semi bbox em fixed

10 deeplab largefov semi bbox rect

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CCVL | Center for Cognition, Vision, and Learning – UCLA | ccvl.stat.ucla.edu Reviews

https://ccvl.stat.ucla.edu

Center for Cognition, Vision, and Learning. Prof Alan L. Yuille, UCLA. Pixelwise-annotated. 400 categories. On 20,000 images. Visual Cortex on Silicon. An NSF Expedition in Computing. Download our new datasets, pixel-wise manually annotated by trained students. Center for Brains, Minds and Machines. CCVL is affiliated to the Center for Brains, Minds and Machines, MIT. Visual Cortex on Silicon. CCVL is member of the NSF Expedition Project Visual Cortex on Silicon . Mathematical Sciences Building, Room 8125.

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ccvl.stat.ucla.edu

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DeepLab-MSc-COCO-LargeFOV | CCVL

http://ccvl.stat.ucla.edu/deeplab-models/deeplab-msc-coco-largefov

DeepLab-MSc-COCO-LargeFOV exploits (1) Multiscale features, (2) extra annotations from MS-COCO dataset (pretrained on MS-COCO, and then fine-tuned on PASCAL), and (3) large Field-Of-View. After DenseCRF, the model yields 73.6% performance on the PASCAL VOC 2012 test set. CRF parameters: bi w = 4, bi xy std = 59, bi rgb std = 5, pos w = 3, pos xy std = 3. Pretrained models and corresponding prototxt files. Please download at here. Developed by Think Up Themes Ltd.

2

People | CCVL

http://ccvl.stat.ucla.edu/people

Prof Alan L. Yuille. Prof Alan L. Yuille. Assistant Professor in the Dept. Statistics, Florida State University. Assistant Professor in the Dept. Chemical Engineering, Florida State University. Professor in the Dept. Psychiatry, UCLA. Professor in the Dept. Computer. Science, Columbia University. Professor in Max Planck Institute. For Biological Cybernetics, German. Microsoft Research Cambridge, England. Professor in the Dept. Engineering Science, University of Oxford. Professor in University of Munich,.

3

DeepLab Models | CCVL

http://ccvl.stat.ucla.edu/deeplab-models

Please see the project website. Developed by Think Up Themes Ltd.

4

Datasets | CCVL

http://ccvl.stat.ucla.edu/datasets

PASCAL Part Segmentation Challenge (website). We provide a platform on which researchers can investigate the performance of semantic part segmentation methods on challenging PASCAL VOC dataset. We build a benchmark, together with an evaluate server. The benchmark currently uses 7 articulated categories. This dataset is a set of additional annotations for PASCAL VOC 2010. It goes beyond the original PASCAL semantic segmentation task by providing annotations for the whole scene (with 400 labels).

5

DeepLab-MSc | CCVL

http://ccvl.stat.ucla.edu/deeplab-models/deeplab-msc

DeepLab-MSc explores a multi-scale prediction method to increase the boundary localization accuracy. Specifically, we attach to the input image and the output of each of the first four max pooling layers a two-layer MLP (first layer: 128 3×3 convolutional filters, second layer: 128 1×1 convolutional filters) whose feature map is concatenated to the main network’s last layer feature map. We only adjust the newly added weights, keeping the other network parameters intact. Please download at here.

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Alan L. Yuille's Homepage

http://www.stat.ucla.edu/~yuille

Alan L. Yuille. Alan L. Yuille. 8967 Math Sciences Building. University of California, Los Angeles. Los Angeles, CA 90095-1554. Yuille AT stat DOT ucla DOT edu. Http:/ ccvl.stat.ucla.edu/. Professor Alan L. Yuille holds a full-time position at Department of Statistics. University of California, Los Angeles. He also holds courtesy appointments at Department of Psychology. Department of Computer Science. He is the director of the UCLA Center for Cognition, Vision, and Learning. UCLA) July 22-August, 2013.

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Center for Cognition, Vision, and Learning. Prof Alan L. Yuille, UCLA. Pixelwise-annotated. 400 categories. On 20,000 images. Visual Cortex on Silicon. An NSF Expedition in Computing. Download our new datasets, pixel-wise manually annotated by trained students. Center for Brains, Minds and Machines. CCVL is affiliated to the Center for Brains, Minds and Machines, MIT. Visual Cortex on Silicon. CCVL is member of the NSF Expedition Project Visual Cortex on Silicon . Mathematical Sciences Building, Room 8125.

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