activity
20152020
most citedPixel-Adaptive Convolutional Neural Networks

20 citations · 32 across the 4 of their papers we have counts for

collaborators

10 papers

cs.CV20204 cited

Generative View Synthesis: From Single-view Semantics to Novel-view Images

Tewodros Habtegebrial, Varun Jampani, Orazio Gallo +1

Content creation, central to applications such as virtual reality, can be a tedious and time-consuming. Recent image synthesis methods simplify this task by offering tools to gener…

cs.CV2020

Bi3D: Stereo Depth Estimation via Binary Classifications

Abhishek Badki, Alejandro Troccoli, Kihwan Kim +3

Stereo-based depth estimation is a cornerstone of computer vision, with state-of-the-art methods delivering accurate results in real time. For several applications such as autonomo…

cs.CV2020

Novel View Synthesis of Dynamic Scenes with Globally Coherent Depths from a Monocular Camera

Jae Shin Yoon, Kihwan Kim, Orazio Gallo +2

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis…

cs.CV2020

Meshlet Priors for 3D Mesh Reconstruction

Abhishek Badki, Orazio Gallo, Jan Kautz +1

Estimating a mesh from an unordered set of sparse, noisy 3D points is a challenging problem that requires carefully selected priors. Existing hand-crafted priors, such as smoothnes…

cs.CV2019

Video Stitching for Linear Camera Arrays

Wei-Sheng Lai, Orazio Gallo, Jinwei Gu +3

Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts. In this work, we propose a wide-baseline…

cs.CV201920 cited

Pixel-Adaptive Convolutional Neural Networks

Hang Su, Varun Jampani, Deqing Sun +3

Convolutions are the fundamental building block of CNNs. The fact that their weights are spatially shared is one of the main reasons for their widespread use, but it also is a majo…