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D-Index & Metrics

Computer Science

D-Index
77
Citations
51541
World Ranking
1230
National Ranking
649

Overview

Jamie Shotton is affiliated with Microsoft in the United States. Their research primarily spans the fields of computer science and engineering, with a focus on specialized areas including computer vision and pattern recognition, artificial intelligence, computational mechanics, control and systems engineering, and signal processing.

Their work covers a range of topics that include:

  • Face recognition and analysis
  • Multimodal machine learning applications
  • Generative adversarial networks and image synthesis
  • 3D shape modeling and analysis
  • Human pose and action recognition
  • Human motion and animation
  • Advanced image and video retrieval techniques

Jamie Shotton has published extensively, with many contributions appearing in prominent venues. Frequent publication sources include:

  • arXiv (Cornell University)
  • 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Lecture Notes in Computer Science

Representative papers showcase Shotton's contributions to computer vision and related fields. Selected recent papers include:

  • Full-Body Motion from a Single Head-Mounted Device: Generating SMPL Poses from Partial Observations, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • FastNeRF: High-Fidelity Neural Rendering at 200FPS, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Model-Based Imitation Learning for Urban Driving, 2022, arXiv (Cornell University)
  • GAIA-1: A Generative World Model for Autonomous Driving, 2023, arXiv (Cornell University)
  • CONFIG: Controllable Neural Face Image Generation, 2020, Lecture Notes in Computer Science

The scientist has collaborated frequently with several researchers, including:

  • M. Kowalski
  • Matthew Johnson
  • Alex Kendall
  • Thomas J. Cashman
  • Sebastian Dziadzio

Best Publications

  • Real-time human pose recognition in parts from single depth images

    Jamie Shotton;Andrew Fitzgibbon;Mat Cook;Toby Sharp

  • The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)

    Bjoern H. Menze;Andras Jakab;Stefan Bauer;Jayashree Kalpathy-Cramer

  • KinectFusion: Real-time dense surface mapping and tracking

    Richard A. Newcombe;Shahram Izadi;Otmar Hilliges;David Molyneaux

  • Real-time human pose recognition in parts from single depth images

    Jamie Shotton;Toby Sharp;Alex Kipman;Andrew Fitzgibbon

  • KinectFusion: real-time 3D reconstruction and interaction using a moving depth camera

    Shahram Izadi;David Kim;Otmar Hilliges;David Molyneaux

  • Enhanced Computer Vision With Microsoft Kinect Sensor: A Review

    Jungong Han;Ling Shao;Dong Xu;Jamie Shotton

  • TextonBoost : joint appearance, shape and context modeling for multi-class object recognition and segmentation

    Jamie Shotton;John Winn;Carsten Rother;Antonio Criminisi

  • Semantic texton forests for image categorization and segmentation

    J. Shotton;M. Johnson;R. Cipolla

  • TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context

    Jamie Shotton;John Winn;Carsten Rother;Antonio Criminisi

  • Segmentation and Recognition Using Structure from Motion Point Clouds

    Gabriel J. Brostow;Jamie Shotton;Julien Fauqueur;Roberto Cipolla

  • Decision Forests: A Unified Framework for Classification, Regression, Density Estimation, Manifold, Learning and Semi-supervised Learning

    Antonio Criminisi;Jamie Shotton;Ender Konukoglu

  • Scene Coordinate Regression Forests for Camera Relocalization in RGB-D Images

    Jamie Shotton;Ben Glocker;Christopher Zach;Shahram Izadi

  • Decision Forests for Computer Vision and Medical Image Analysis

    A. Criminisi;J. Shotton

  • Learning 6D Object Pose Estimation Using 3D Object Coordinates

    Eric Brachmann;Alexander Krull;Frank Michel;Stefan Gumhold

  • Multiscale Categorical Object Recognition Using Contour Fragments

    J. Shotton;A. Blake;R. Cipolla

  • Efficient Human Pose Estimation from Single Depth Images

    Jamie Shotton;Ross Girshick;Andrew Fitzgibbon;Toby Sharp

  • DSAC — Differentiable RANSAC for Camera Localization

    Eric Brachmann;Alexander Krull;Sebastian Nowozin;Jamie Shotton

  • Accurate, Robust, and Flexible Real-time Hand Tracking

    Toby Sharp;Cem Keskin;Duncan Robertson;Jonathan Taylor

  • Efficient regression of general-activity human poses from depth images

    Ross Girshick;Jamie Shotton;Pushmeet Kohli;Antonio Criminisi

  • Contour-based learning for object detection

    J. Shotton;A. Blake;R. Cipolla

Frequent Co-Authors

Antonio Criminisi
Antonio Criminisi Microsoft (United States)
Pushmeet Kohli
Pushmeet Kohli DeepMind (United Kingdom)
Shahram Izadi
Shahram Izadi Google (United States)
David Kim
David Kim Microsoft (United States)
Otmar Hilliges
Otmar Hilliges ETH Zurich
John Winn
John Winn Microsoft (United States)
Carsten Rother
Carsten Rother Heidelberg University
Roberto Cipolla
Roberto Cipolla University of Cambridge
Andrew Blake
Andrew Blake University of Cambridge

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