A Comprehensive Performance Evaluation of Deformable Face Tracking "In-the-Wild"
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Abstract (arXiv)
Recently, technologies such as face detection, facial landmark localisation and face recognition and verification have matured enough to provide effective and efficient solutions for imagery captured under arbitrary conditions (referred to as "in-the-wild"). This is partially attributed to the fact that comprehensive "in-the-wild" benchmarks have been developed for face detection, landmark localisation and recognition/verification. A very important technology that has not been thoroughly evaluated yet is deformable face tracking "in-the-wild". Until now, the performance has mainly been assessed qualitatively by visually assessing the result of a deformable face tracking technology on short videos. In this paper, we perform the first, to the best of our knowledge, thorough evaluation of state-of-the-art deformable face tracking pipelines using the recently introduced 300VW benchmark. We evaluate many different architectures focusing mainly on the task of on-line deformable face tracking. In particular, we compare the following general strategies: (a) generic face detection plus generic facial landmark localisation, (b) generic model free tracking plus generic facial landmark localisation, as well as (c) hybrid approaches using state-of-the-art face detection, model free tracking and facial landmark localisation technologies. Our evaluation reveals future avenues for further research on the topic.
Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Mar 2016.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 1.
5 papers.
- 2021Supervision by Registration and Triangulation for Landmark Detectioncited by 30
- 2021Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometrycited by 27
- 2022Leveraging Deepfakes to Close the Domain Gap between Real and Synthetic Images in Facial Capture Pipelinescited by 4
- 2024Democratizing the Creation of Animatable Facial Avatarscited by 1
- 20231DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Trackingcited by 0
- 2024Democratizing the Creation of Animatable Facial Avatars29 Jan 2024
- 20231DFormer: a Transformer Architecture Learning 1D Landmark Representations for Facial Landmark Tracking1 Nov 2023
- 2022Leveraging Deepfakes to Close the Domain Gap between Real and Synthetic Images in Facial Capture Pipelines22 Apr 2022
- 2021Synergy between 3DMM and 3D Landmarks for Accurate 3D Facial Geometry19 Oct 2021
- 2021Supervision by Registration and Triangulation for Landmark Detection25 Jan 2021