CVPR 2017 Oral Our network uses a dilation-based 3D context module to efficiently expand the receptive field and enable 3D context learning.
3DOR 2017 This track provides a benchmark to evaluate large-scale 3D shape retrieval based on the ShapeNet dataset.
arXiv 2016 We introduce the first domain adaptive semantic segmentation method, proposing an unsupervised adversarial approach to pixel prediction problems.
Siggraph 2016 We seek a relative quality measure within a series of photos taken of the same scene, which can be used for automatic photo triage.
ICLR 2016 We study dilated convolution in depth. It has become a foundamental network operation.
arXiv 2015 We propose to amplify human effort through a partially automated labeling scheme, leveraging deep learning with humans in the loop.
CVPR 2015 We propose an automatic algorithm for global alignment of LiDAR data collected with Google Street View cars in urban environments.
CVPR 2015 Oral We propose to represent a geometric 3D shape as a probability distribution of binary variables on a 3D voxel grid.
arXiv 2015 We present ShapeNet: a richly-annotated, large-scale repository of shapes represented by 3D CAD models of objects.
CVPR 2014 We have discovered that 3D reconstruction can be achieved from a single still photographic capture due to accidental motions of the photographer.
Siggraph 2012 This paper presents a data-driven approach for synthesizing the 6D hand gesture data for users of low-quality input devices.
Comparing seven spectral methods for interpolation and for solving the Poisson equation in a disk: Zernike polynomials, Logan–Shepp ridge polynomials, Chebyshev–Fourier Series, cylindrical Robert functions, Bessel–Fourier expansions, square-to-disk conformal mapping and radial basis functions
Journal of Computational Physics 2011 We compare seven different strategies for computing spectrally-accurate approximations or differential equation solutions in a disk.