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20162021
most citedGenerative Sparse Detection Networks for 3D Single-shot Object Detection

6 citations · 11 across the 4 of their papers we have counts for

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11 papers · 1 filter

cs.CV2021

Self-Calibrating Neural Radiance Fields

Yoonwoo Jeong, Seokjun Ahn, Christopher Choy +3

In this work, we propose a camera self-calibration algorithm for generic cameras with arbitrary non-linear distortions. We jointly learn the geometry of the scene and the accurate…

cs.CV20215 cited

DiscoBox: Weakly Supervised Instance Segmentation and Semantic Correspondence from Box Supervision

Shiyi Lan, Zhiding Yu, Christopher Choy +5

We introduce DiscoBox, a novel framework that jointly learns instance segmentation and semantic correspondence using bounding box supervision. Specifically, we propose a self-ensem…

cs.CV20206 cited

Generative Sparse Detection Networks for 3D Single-shot Object Detection

JunYoung Gwak, Christopher Choy, Silvio Savarese

3D object detection has been widely studied due to its potential applicability to many promising areas such as robotics and augmented reality. Yet, the sparse nature of the 3D data…

cs.CV2020

High-dimensional Convolutional Networks for Geometric Pattern Recognition

Christopher Choy, Junha Lee, Rene Ranftl +2

Many problems in science and engineering can be formulated in terms of geometric patterns in high-dimensional spaces. We present high-dimensional convolutional networks (ConvNets)…

cs.CV2020

Deep Global Registration

Christopher Choy, Wei Dong, Vladlen Koltun

We present Deep Global Registration, a differentiable framework for pairwise registration of real-world 3D scans. Deep global registration is based on three modules: a 6-dimensiona…

cs.CV2020

SceneCAD: Predicting Object Alignments and Layouts in RGB-D Scans

Armen Avetisyan, Tatiana Khanova, Christopher Choy +3

We present a novel approach to reconstructing lightweight, CAD-based representations of scanned 3D environments from commodity RGB-D sensors. Our key idea is to jointly optimize fo…