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MagicEyes: A Large Scale Eye Gaze Estimation Dataset for Mixed Reality
Zhengyang Wu, Srivignesh Rajendran, Tarrence van As +3
With the emergence of Virtual and Mixed Reality (XR) devices, eye tracking has received significant attention in the computer vision community. Eye gaze estimation is a crucial com…
Scan2Plan: Efficient Floorplan Generation from 3D Scans of Indoor Scenes
Ameya Phalak, Vijay Badrinarayanan, Andrew Rabinovich
We introduce Scan2Plan, a novel approach for accurate estimation of a floorplan from a 3D scan of the structural elements of indoor environments. The proposed method incorporates a…
Atlas: End-to-End 3D Scene Reconstruction from Posed Images
Zak Murez, Tarrence van As, James Bartolozzi +3
We present an end-to-end 3D reconstruction method for a scene by directly regressing a truncated signed distance function (TSDF) from a set of posed RGB images. Traditional approac…
DELTAS: Depth Estimation by Learning Triangulation And densification of Sparse points
Ayan Sinha, Zak Murez, James Bartolozzi +2
Multi-view stereo (MVS) is the golden mean between the accuracy of active depth sensing and the practicality of monocular depth estimation. Cost volume based approaches employing 3…
SuperGlue: Learning Feature Matching with Graph Neural Networks
Paul-Edouard Sarlin, Daniel DeTone, Tomasz Malisiewicz +1
This paper introduces SuperGlue, a neural network that matches two sets of local features by jointly finding correspondences and rejecting non-matchable points. Assignments are est…
Efficient 2.5D Hand Pose Estimation via Auxiliary Multi-Task Training for Embedded Devices
Prajwal Chidananda, Ayan Sinha, Adithya Rao +2
2D Key-point estimation is an important precursor to 3D pose estimation problems for human body and hands. In this work, we discuss the data, architecture, and training procedure n…
EyeNet: A Multi-Task Network for Off-Axis Eye Gaze Estimation and User Understanding
Zhengyang Wu, Srivignesh Rajendran, Tarrence van As +3
Eye gaze estimation and simultaneous semantic understanding of a user through eye images is a crucial component in Virtual and Mixed Reality; enabling energy efficient rendering, m…
DeepPerimeter: Indoor Boundary Estimation from Posed Monocular Sequences
Ameya Phalak, Zhao Chen, Darvin Yi +3
We present DeepPerimeter, a deep learning based pipeline for inferring a full indoor perimeter (i.e. exterior boundary map) from a sequence of posed RGB images. Our method relies o…
Self-Improving Visual Odometry
Daniel DeTone, Tomasz Malisiewicz, Andrew Rabinovich
We propose a self-supervised learning framework that uses unlabeled monocular video sequences to generate large-scale supervision for training a Visual Odometry (VO) frontend, a ne…
Estimating Depth from RGB and Sparse Sensing
Zhao Chen, Vijay Badrinarayanan, Gilad Drozdov +1
We present a deep model that can accurately produce dense depth maps given an RGB image with known depth at a very sparse set of pixels. The model works simultaneously for both ind…
SuperPoint: Self-Supervised Interest Point Detection and Description
Daniel DeTone, Tomasz Malisiewicz, Andrew Rabinovich
This paper presents a self-supervised framework for training interest point detectors and descriptors suitable for a large number of multiple-view geometry problems in computer vis…
GradNorm: Gradient Normalization for Adaptive Loss Balancing in Deep Multitask Networks
Zhao Chen, Vijay Badrinarayanan, Chen-Yu Lee +1
Deep multitask networks, in which one neural network produces multiple predictive outputs, can offer better speed and performance than their single-task counterparts but are challe…
Toward Geometric Deep SLAM
Daniel DeTone, Tomasz Malisiewicz, Andrew Rabinovich
We present a point tracking system powered by two deep convolutional neural networks. The first network, MagicPoint, operates on single images and extracts salient 2D points. The e…
RoomNet: End-to-End Room Layout Estimation
Chen-Yu Lee, Vijay Badrinarayanan, Tomasz Malisiewicz +1
This paper focuses on the task of room layout estimation from a monocular RGB image. Prior works break the problem into two sub-tasks: semantic segmentation of floor, walls, ceilin…
Deep Cuboid Detection: Beyond 2D Bounding Boxes
Debidatta Dwibedi, Tomasz Malisiewicz, Vijay Badrinarayanan +1
We present a Deep Cuboid Detector which takes a consumer-quality RGB image of a cluttered scene and localizes all 3D cuboids (box-like objects). Contrary to classical approaches wh…
Deep Image Homography Estimation
Daniel DeTone, Tomasz Malisiewicz, Andrew Rabinovich
We present a deep convolutional neural network for estimating the relative homography between a pair of images. Our feed-forward network has 10 layers, takes two stacked grayscale…
ParseNet: Looking Wider to See Better
Wei Liu, Andrew Rabinovich, Alexander C. Berg
We present a technique for adding global context to deep convolutional networks for semantic segmentation. The approach is simple, using the average feature for a layer to augment…
Training Deep Neural Networks on Noisy Labels with Bootstrapping
Scott Reed, Honglak Lee, Dragomir Anguelov +3
Current state-of-the-art deep learning systems for visual object recognition and detection use purely supervised training with regularization such as dropout to avoid overfitting.…
Going Deeper with Convolutions
Christian Szegedy, Wei Liu, Yangqing Jia +6
We propose a deep convolutional neural network architecture codenamed "Inception", which was responsible for setting the new state of the art for classification and detection in th…
Using Web Co-occurrence Statistics for Improving Image Categorization
Samy Bengio, Jeff Dean, Dumitru Erhan +5
Object recognition and localization are important tasks in computer vision. The focus of this work is the incorporation of contextual information in order to improve object recogni…