An overview on the evaluated video retrieval tasks at TRECVID 2022

no code implementations • 22 Jun 2023 • George Awad, Keith Curtis, Asad Butt, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Eliot Godard, Lukas Diduch, Jeffrey Liu, Yvette Graham, Georges Quenot

The TREC Video Retrieval Evaluation (TRECVID) is a TREC-style video analysis and retrieval evaluation with the goal of promoting progress in research and development of content-based exploitation and retrieval of information from digital video via open, tasks-based evaluation supported by metrology.

Ad-hoc video search Retrieval +2

TRECVID 2020: A comprehensive campaign for evaluating video retrieval tasks across multiple application domains

no code implementations • 27 Apr 2021 • George Awad, Asad A. Butt, Keith Curtis, Jonathan Fiscus, Afzal Godil, Yooyoung Lee, Andrew Delgado, Jesse Zhang, Eliot Godard, Baptiste Chocot, Lukas Diduch, Jeffrey Liu, Alan F. Smeaton, Yvette Graham, Gareth J. F. Jones, Wessel Kraaij, Georges Quenot

In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1.

Ad-hoc video search Instance Search +3

TRECVID 2019: An Evaluation Campaign to Benchmark Video Activity Detection, Video Captioning and Matching, and Video Search & Retrieval

no code implementations • 21 Sep 2020 • George Awad, Asad A. Butt, Keith Curtis, Yooyoung Lee, Jonathan Fiscus, Afzal Godil, Andrew Delgado, Jesse Zhang, Eliot Godard, Lukas Diduch, Alan F. Smeaton, Yvette Graham, Wessel Kraaij, Georges Quenot

The TREC Video Retrieval Evaluation (TRECVID) 2019 was a TREC-style video analysis and retrieval evaluation, the goal of which remains to promote progress in research and development of content-based exploitation and retrieval of information from digital video via open, metrics-based evaluation.

Action Detection Activity Detection +5

Shape retrieval of non-rigid 3d human models

no code implementations • 1 Mar 2020 • David Pickup, Xianfang Sun, Paul L. Rosin, Ralph R. Martin, Z Cheng, Zhouhui Lian, Masaki Aono, A. Ben Hamza, A Bronstein, M Bronstein, S Bu, Umberto Castellani, S Cheng, Valeria Garro, Andrea Giachetti, Afzal Godil, Luca Isaia, J. Han, Henry Johan, L Lai, Bo Li, C. Li, Haisheng Li, Roee Litman, X. Liu, Z Liu, Yijuan Lu, L. Sun, G Tam, Atsushi Tatsuma, J. Ye

In addition, further participants have also taken part, and we provide extra analysis of the retrieval results.

3D Shape Classification 3D Shape Retrieval +1

Face Recognition using 3D Facial Shape and Color Map Information: Comparison and Combination

no code implementations • 13 May 2011 • Afzal Godil, Sandy Ressler, Patrick Grother

In this paper, we investigate the use of 3D surface geometry for face recognition and compare it to one based on color map information.

Face Recognition