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The 2017 Hands in the Million Challenge on 3D Hand Pose Estimation

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arxiv 1707.02237 v1 pith:M6G3FZZH submitted 2017-07-07 cs.CV

classification cs.CV
keywords challengehandhandsestimationevaluationposeactioncompetition
verification ladder T0 review T1 audit T2 compute T3 formal

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We present the 2017 Hands in the Million Challenge, a public competition designed for the evaluation of the task of 3D hand pose estimation. The goal of this challenge is to assess how far is the state of the art in terms of solving the problem of 3D hand pose estimation as well as detect major failure and strength modes of both systems and evaluation metrics that can help to identify future research directions. The challenge follows up the recent publication of BigHand2.2M and First-Person Hand Action datasets, which have been designed to exhaustively cover multiple hand, viewpoint, hand articulation, and occlusion. The challenge consists of a standardized dataset, an evaluation protocol for two different tasks, and a public competition. In this document we describe the different aspects of the challenge and, jointly with the results of the participants, it will be presented at the 3rd International Workshop on Observing and Understanding Hands in Action, HANDS 2017, with ICCV 2017.

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Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videos

    cs.CV 2024-11 conditional novelty 7.0 of 10

    HOT3D releases 833 minutes of hardware-synchronized, egocentric multi-view video from real headsets with motion-capture ground truth for hands and objects, and shows multi-view baselines outperform single-view baselin...

  2. A2J: Anchor-to-Joint Regression Network for 3D Articulated Pose Estimation from a Single Depth Image

    cs.CV 2019-08 conditional novelty 6.0 of 10

    A2J uses dense anchor points on a depth image to regress 3D joint positions via weighted aggregation, achieving real-time speed and competitive accuracy.

  3. Survey on Hand Gesture Recognition from Visual Input

    cs.CV 2025-01 conditional novelty 4.0 of 10

    A structured survey of recent hand gesture recognition from camera input, with a taxonomy of methods, datasets, metrics, and open problems.

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