Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Khot, Tejas"'
This work focuses on low bitrate video streaming scenarios (e.g. 50 - 200Kbps) where the video quality is severely compromised. We present a family of novel deep generative models for enhancing perceptual video quality of such streams by performing s
Externí odkaz:
http://arxiv.org/abs/2211.12604
Autor:
Khot, Tejas, Agrawal, Shubham, Tulsiani, Shubham, Mertz, Christoph, Lucey, Simon, Hebert, Martial
We present a learning based approach for multi-view stereopsis (MVS). While current deep MVS methods achieve impressive results, they crucially rely on ground-truth 3D training data, and acquisition of such precise 3D geometry for supervision is a ma
Externí odkaz:
http://arxiv.org/abs/1905.02706
Shape completion, the problem of estimating the complete geometry of objects from partial observations, lies at the core of many vision and robotics applications. In this work, we propose Point Completion Network (PCN), a novel learning-based approac
Externí odkaz:
http://arxiv.org/abs/1808.00671
Problems at the intersection of vision and language are of significant importance both as challenging research questions and for the rich set of applications they enable. However, inherent structure in our world and bias in our language tend to be a
Externí odkaz:
http://arxiv.org/abs/1612.00837
Autor:
Goyal, Yash1 ygoyal@gatech.edu, Khot, Tejas2 tkhot@andrew.cmu.edu, Agrawal, Aishwarya1 aishwarya@gatech.edu, Summers-Stay, Douglas3 douglas.a.summers-stay.civ@mail.mil, Batra, Dhruv1,4 dbatra@gatech.edu, Parikh, Devi1,4 parikh@gatech.edu
Publikováno v:
International Journal of Computer Vision. Apr2019, Vol. 127 Issue 4, p398-414. 17p. 4 Diagrams, 5 Charts, 10 Graphs.
