H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 31 Citations 5,950 92 World Ranking 7958 National Ranking 74

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Min Sun mainly investigates Artificial intelligence, Computer vision, Pose, Pattern recognition and Object. His Artificial intelligence research incorporates elements of Machine learning, Adaptation and Natural language processing. His Adaptation research focuses on subjects like Adversarial system, which are linked to Image.

When carried out as part of a general Computer vision research project, his work on Image processing, Image-based modeling and rendering and Markov random field is frequently linked to work in Markov process and Depth perception, therefore connecting diverse disciplines of study. Min Sun focuses mostly in the field of Pose, narrowing it down to topics relating to Object detection and, in certain cases, Object model. His study in the fields of Object detector under the domain of Object overlaps with other disciplines such as Cinematography.

His most cited work include:

  • Make3D: Learning 3D Scene Structure from a Single Still Image (1205 citations)
  • No More Discrimination: Cross City Adaptation of Road Scene Segmenters (186 citations)
  • Articulated part-based model for joint object detection and pose estimation (176 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Artificial intelligence, Computer vision, Machine learning, Pattern recognition and Image. Object, Equirectangular projection, Segmentation, Object detection and Pose are among the areas of Artificial intelligence where Min Sun concentrates his study. Min Sun has included themes like Object model, Inference and Branch and bound in his Pose study.

In his works, Min Sun conducts interdisciplinary research on Computer vision and Depth perception. Other disciplines of study, such as Supervised learning and Markov random field, are mixed together with his Depth perception studies. His work focuses on many connections between Pattern recognition and other disciplines, such as Depth map, that overlap with his field of interest in Feature.

He most often published in these fields:

  • Artificial intelligence (80.15%)
  • Computer vision (45.80%)
  • Machine learning (15.27%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (80.15%)
  • Computer vision (45.80%)
  • Equirectangular projection (11.45%)

In recent papers he was focusing on the following fields of study:

Min Sun focuses on Artificial intelligence, Computer vision, Equirectangular projection, Benchmark and Image. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Pattern recognition. His studies in Machine learning integrate themes in fields like Inference and Forgetting.

His Equirectangular projection study combines topics in areas such as Depth map, Cube mapping, RANSAC and Distortion. His Benchmark research incorporates themes from Video tracking and Minimum bounding box. His research in Image intersects with topics in Object detection and Bounding overwatch.

Between 2019 and 2021, his most popular works were:

  • BiFuse: Monocular 360 Depth Estimation via Bi-Projection Fusion (10 citations)
  • Controllable Image Synthesis via SegVAE. (7 citations)
  • 360SD-Net: 360° Stereo Depth Estimation with Learnable Cost Volume (7 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Computer vision

Min Sun spends much of his time researching Artificial intelligence, Equirectangular projection, Computer vision, Depth map and Pixel. His study looks at the relationship between Artificial intelligence and fields such as Machine learning, as well as how they intersect with chemical problems. His work deals with themes such as Monocular, Feature, Face, Distortion and Cube mapping, which intersect with Depth map.

His research integrates issues of Image editing, Object, Translation, RGB color model and Pattern recognition in his study of Pixel. His Panorama research includes themes of Annotation, Robotics and Virtual reality, Human–computer interaction. Domain is integrated with Class, Object detection, Sight, Image and Bounding overwatch in his study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Top Publications

Make3D: Learning 3D Scene Structure from a Single Still Image

A. Saxena;Min Sun;A.Y. Ng.
IEEE Transactions on Pattern Analysis and Machine Intelligence (2009)

1665 Citations

Learning 3-D Scene Structure from a Single Still Image

A. Saxena;Min Sun;A.Y. Ng.
international conference on computer vision (2007)

266 Citations

A Unified Model for Extractive and Abstractive Summarization using Inconsistency Loss

Wan Ting Hsu;Chieh-Kai Lin;Ming-Ying Lee;Kerui Min.
meeting of the association for computational linguistics (2018)

265 Citations

No More Discrimination: Cross City Adaptation of Road Scene Segmenters

Yi-Hsin Chen;Wei-Yu Chen;Yu-Ting Chen;Bo-Cheng Tsai.
international conference on computer vision (2017)

236 Citations

Articulated part-based model for joint object detection and pose estimation

Min Sun;Silvio Savarese.
international conference on computer vision (2011)

206 Citations

Conditional regression forests for human pose estimation

Min Sun;Pushmeet Kohli;Jamie Shotton.
computer vision and pattern recognition (2012)

204 Citations

Learning a dense multi-view representation for detection, viewpoint classification and synthesis of object categories

Hao Su;Min Sun;Li Fei-Fei;Silvio Savarese.
international conference on computer vision (2009)

199 Citations

A multi-view probabilistic model for 3D object classes

Min Sun;Hao Su;Silvio Savarese;Li Fei-Fei.
computer vision and pattern recognition (2009)

161 Citations

Depth-encoded hough voting for joint object detection and shape recovery

Min Sun;Gary Bradski;Bing-Xin Xu;Silvio Savarese.
european conference on computer vision (2010)

152 Citations

Ranking Domain-Specific Highlights by Analyzing Edited Videos

Min Sun;Ali Farhadi;Steven M. Seitz.
european conference on computer vision (2014)

145 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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Top Scientists Citing Min Sun

Luc Van Gool

Luc Van Gool

ETH Zurich

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Dacheng Tao

Dacheng Tao

University of Sydney

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Stanford University

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Ashutosh Saxena

Ashutosh Saxena

Cornell University

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Chunhua Shen

Chunhua Shen

University of Adelaide

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Ming-Hsuan Yang

Ming-Hsuan Yang

University of California, Merced

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Kristen Grauman

Kristen Grauman

Facebook (United States)

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Juergen Gall

Juergen Gall

University of Bonn

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Zhou Zhao

Zhou Zhao

Zhejiang University

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Alan L. Yuille

Alan L. Yuille

Johns Hopkins University

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Martial Hebert

Martial Hebert

Carnegie Mellon University

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Bernt Schiele

Bernt Schiele

Max Planck Institute for Informatics

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Jiebo Luo

Jiebo Luo

University of Rochester

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Raquel Urtasun

Raquel Urtasun

University of Toronto

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Kwanghoon Sohn

Kwanghoon Sohn

Yonsei University

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