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20172021
most citedTEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding

4 citations · 6 across the 7 of their papers we have counts for

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10 papers · 1 filter

cs.CV20214 cited

TEAM-Net: Multi-modal Learning for Video Action Recognition with Partial Decoding

Zhengwei Wang, Qi She, Aljosa Smolic

Most of existing video action recognition models ingest raw RGB frames. However, the raw video stream requires enormous storage and contains significant temporal redundancy. Video…

cs.CV2021

Foreground color prediction through inverse compositing

Sebastian Lutz, Aljosa Smolic

In natural image matting, the goal is to estimate the opacity of the foreground object in the image. This opacity controls the way the foreground and background is blended in trans…

cs.CV2021

DuctTake: Spatiotemporal Video Compositing

Jan Rueegg, Oliver Wang, Aljoscha Smolic +1

DuctTake is a system designed to enable practical compositing of multiple takes of a scene into a single video. Current industry solutions are based around object segmentation, a h…

cs.CV20202 cited

CatNet: Class Incremental 3D ConvNets for Lifelong Egocentric Gesture Recognition

Zhengwei Wang, Qi She, Tejo Chalasani +1

Egocentric gestures are the most natural form of communication for humans to interact with wearable devices such as VR/AR helmets and glasses. A major issue in such scenarios for r…

cs.CV2019

Simultaneous Segmentation and Recognition: Towards more accurate Ego Gesture Recognition

Tejo Chalasani, Aljosa Smolic

Ego hand gestures can be used as an interface in AR and VR environments. While the context of an image is important for tasks like scene understanding, object recognition, image ca…

cs.CV2019

DublinCity: Annotated LiDAR Point Cloud and its Applications

S. M. Iman Zolanvari, Susana Ruano, Aakanksha Rana +4

Scene understanding of full-scale 3D models of an urban area remains a challenging task. While advanced computer vision techniques offer cost-effective approaches to analyse 3D urb…