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GTC ON-DEMAND

Presentation
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Abstract:
We'll introduce attendees to a new deep learning approach to object-localization. Instead of bounding boxes, our network estimates the center pixel locations for a variable number of targets in a scene while simultaneously extracting a characteristic feature-set. We'll outline the overall approach and describe the underlying network architecture and training. We'll also present the results of our network as applied to the cars overhead with context dataset and discuss the current and future possibilities of this approach.
We'll introduce attendees to a new deep learning approach to object-localization. Instead of bounding boxes, our network estimates the center pixel locations for a variable number of targets in a scene while simultaneously extracting a characteristic feature-set. We'll outline the overall approach and describe the underlying network architecture and training. We'll also present the results of our network as applied to the cars overhead with context dataset and discuss the current and future possibilities of this approach.  Back
 
Topics:
AI and DL Research, Computer Vision
Type:
Talk
Event:
GTC Silicon Valley
Year:
2018
Session ID:
S8191
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