no code implementations • 9 Dec 2020 • Rui Fan, Christopher Bowd, Nicole Brye, Mark Christopher, Robert N. Weinreb, David Kriegman, Linda M. Zangwill
Our proposed multi-task Siamese network (MTSN) can employ any backbone CNN, and we demonstrate with four backbone CNNs that its accuracy with limited training data approaches the accuracy of backbone CNNs trained with a dataset that is 50 times larger.
no code implementations • 9 Aug 2020 • Sai Bi, Zexiang Xu, Pratul Srinivasan, Ben Mildenhall, Kalyan Sunkavalli, Miloš Hašan, Yannick Hold-Geoffroy, David Kriegman, Ravi Ramamoorthi
We combine this representation with a physically-based differentiable ray marching framework that can render images from a neural reflectance field under any viewpoint and light.
no code implementations • ECCV 2020 • Sai Bi, Zexiang Xu, Kalyan Sunkavalli, Miloš Hašan, Yannick Hold-Geoffroy, David Kriegman, Ravi Ramamoorthi
We also show that our learned reflectance volumes are editable, allowing for modifying the materials of the captured scenes.
no code implementations • CVPR 2020 • Sai Bi, Zexiang Xu, Kalyan Sunkavalli, David Kriegman, Ravi Ramamoorthi
We introduce a novel learning-based method to reconstruct the high-quality geometry and complex, spatially-varying BRDF of an arbitrary object from a sparse set of only six images captured by wide-baseline cameras under collocated point lighting.
1 code implementation • 7 Jun 2019 • Iljung S. Kwak, Jian-Zhong Guo, Adam Hantman, David Kriegman, Kristin Branson
In this work, we address the problem of precisely localizing key frames of an action, for example, the precise time that a pitcher releases a baseball, or the precise time that a crowd begins to applaud.
no code implementations • CVPR 2018 • Zak Murez, Soheil Kolouri, David Kriegman, Ravi Ramamoorthi, Kyungnam Kim
This is achieved by adding extra networks and losses that help regularize the features extracted by the backbone encoder network.
no code implementations • ICCV 2017 • Jiandong Tian, Zachary Murez, Tong Cui, Zhen Zhang, David Kriegman, Ravi Ramamoorthi
First, we present a new single image restoration algorithm which removes backscatter and attenuation from images better than existing methods, and apply it to each view in the light field.
1 code implementation • 26 May 2016 • Jameson Merkow, David Kriegman, Alison Marsden, Zhuowen Tu
In this work, we present a novel 3D-Convolutional Neural Network (CNN) architecture called I2I-3D that predicts boundary location in volumetric data.
no code implementations • ICCV 2015 • Zak Murez, Tali treibitz, Ravi Ramamoorthi, David Kriegman
Next, we model the blur due to scattering of light from the object.
no code implementations • ICCV 2015 • Michael J. Wilber, Iljung S. Kwak, David Kriegman, Serge Belongie
This paper presents our work on "SNaCK," a low-dimensional concept embedding algorithm that combines human expertise with automatic machine similarity kernels.
no code implementations • NeurIPS 2012 • Andrew Ziegler, Eric Christiansen, David Kriegman, Serge J. Belongie
Keypoint matching between pairs of images using popular descriptors like SIFT or a faster variant called SURF is at the heart of many computer vision algorithms including recognition, mosaicing, and structure from motion.