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most citedMethods for Interpreting and Understanding Deep Neural Networks

2.8k citations

Showing 2019 · cs.CVShow all

11 papers · 2 filters

cs.CV2019

A Quantum Computational Approach to Correspondence Problems on Point Sets

Vladislav Golyanik, Christian Theobalt

Modern adiabatic quantum computers (AQC) are already used to solve difficult combinatorial optimisation problems in various domains of science. Currently, only a few applications o…

cs.CV2019★ 63 cited

Neural Style-Preserving Visual Dubbing

Hyeongwoo Kim, Mohamed Elgharib, Michael Zollhöfer +4

Dubbing is a technique for translating video content from one language to another. However, state-of-the-art visual dubbing techniques directly copy facial expressions from source…

cs.CV2019

Universal Physical Camouflage Attacks on Object Detectors

Lifeng Huang, Chengying Gao, Yuyin Zhou +4

In this paper, we study physical adversarial attacks on object detectors in the wild. Previous works mostly craft instance-dependent perturbations only for rigid or planar objects.…

cs.CV2019★ 5 cited

Intrinsic Dynamic Shape Prior for Fast, Sequential and Dense Non-Rigid Structure from Motion with Detection of Temporally-Disjoint Rigidity

Vladislav Golyanik, André Jonas, Didier Stricker +1

While dense non-rigid structure from motion (NRSfM) has been extensively studied from the perspective of the reconstructability problem over the recent years, almost no attempts ha…

cs.CV2019★ 3 cited

EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera

Lan Xu, Weipeng Xu, Vladislav Golyanik +3

The high frame rate is a critical requirement for capturing fast human motions. In this setting, existing markerless image-based methods are constrained by the lighting requirement…

cs.CV2019★ 25 cited

Real-Time Global Illumination Decomposition of Videos

Abhimitra Meka, Mohammad Shafiei, Michael Zollhoefer +2

We propose the first approach for the decomposition of a monocular color video into direct and indirect illumination components in real time. We retrieve, in separate layers, the c…