PPT-Feedforward semantic segmentation with zoom-out features

Mostajabi Yadollahpour and Shakhnarovich Toyota Technological Institute at Chicago Main Ideas Casting semantic segmentation as classifying a set of superpixels Extracting CNN features from different levels of spatial context around the . 1 CD6 SE Fig 1 CD XT SE Fig 1 CD8 SE Fig 1 CD ransport brPage 3br 325 1015 Reading 325 325 Fig 3 17 59 57 Fig 2 1 1 1 brPage 4br Cyrus CD 6 SE 2 CD 8 SE 2 CD XT SE 2 CD T TRANSPORT User Instructions 1 IMPORTANT Read before operating this equipme brPage 1br OUT 12 OUT 34 OUT 56 OUT 7 OUT KICK SNARE OM OM HI GAN UKELELE ZITHER BANJO ELEC GTR OUST GTR OH R OH L OWBELL GAN HI VO AL BASS DIRE BASS MP SOFT S N R SOFT S N L AN G S NTH THERE doc Operational Procedure. In the box. All H2 Zoom kits contain. 1 GB SD Card. Mic. Clip Adaptor. Wind Screen. Earbuds. USB Cable. AC Adaptor. Stereo Y Cable. Manual. Audio File Format. All . H2 Zoom’s will be preset to record in MP3 format. At 320kb/s you will get almost 7 hours of recording time on the 1 GB SD Card.. By: A’laa . Kryeem. Lecturer: . Hagit. Hel-Or. What is . Segmentation from . Examples. ?. Segment an image based on one (or more) correctly segmented image(s) assumed to be from the same . domain. -concepts and facts. -several similar models describe . the organization . of semantic . memory. 1) Collins & . Quillian’s. Hierarchical Network Model. -nodes to represent individual items, ideas, organized hierarchically. Anurag Arnab. Collaborators: . sadeep. . Jayasumana. , . shuai. . zheng. , Philip . torr. Introduction. Semantic Segmentation. Labelling every pixel in an image. A key part of Scene Understanding. Second-Order Pooling. João Carreira. 1,2. , Rui Caseiro. 1. , Jorge Batista. 1. , Cristian Sminchisescu. 2. 1. . Institute of Systems and Robotics. ,. . University of Coimbra. 2. . Faculty of Mathematics and Natural . 2015. 2. 12.. Jeany Son. References. Bottom-up Segmentation for Top-down . Detection, CVPR 2013. Segmentation-aware Deformable Part Models, CVPR 2014. 2. Prior Works on Segmentation & Recognition. person 1. person 2. horse 1. horse 2. R-CNN: Regions with CNN features. Input. image. Extract region. proposals (~2k / image). Compute CNN. features. Classify regions. (linear SVM). Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation. Introduction. Semantic Role Labeling. Agent. Theme. Predicate. Location. Can we figure out that these have the same meaning?. XYZ . corporation . bought. the . stock.. They . sold. the stock to XYZ . https://support.zoom.us/hc/en-us/articles/206476313. Options for Breakout Rooms. How to broadcast to Breakout Rooms. How to pre-assign Breakout rooms . before meeting. Altered time for OH tomorrow: 9:00-10:00 am.. Please complete mid-semester feedback. Semantic Segmentation. The Task. person. grass. trees. motorbike. road. Evaluation metric. Pixel classification!. Accuracy?. Juan Carlos . Niebles. and Ranjay Krishna. Stanford Vision and Learning Lab. What we will learn today. Introduction to segmentation and clustering. Gestalt theory for perceptual grouping. Agglomerative clustering.