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

arXiv 2104.13473 ↗First posted 27 Apr 2021cs.CV cs.AIcited by 16

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Abstract (arXiv)

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, metrics-based evaluation. Over the last twenty years this effort has yielded a better understanding of how systems can effectively accomplish such processing and how one can reliably benchmark their performance. TRECVID has been funded by NIST (National Institute of Standards and Technology) and other US government agencies. In addition, many organizations and individuals worldwide contribute significant time and effort. TRECVID 2020 represented a continuation of four tasks and the addition of two new tasks. In total, 29 teams from various research organizations worldwide completed one or more of the following six tasks: 1. Ad-hoc Video Search (AVS), 2. Instance Search (INS), 3. Disaster Scene Description and Indexing (DSDI), 4. Video to Text Description (VTT), 5. Activities in Extended Video (ActEV), 6. Video Summarization (VSUM). This paper is an introduction to the evaluation framework, tasks, data, and measures used in the evaluation campaign.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). Builds on 5 of its 29 references that are in the map. First posted on arXiv 27 Apr 2021.

Builds on

5 of 29 references.

References · 5

  1. 2014CIDEr: Consensus-based Image Description Evaluationcited by 2,027
  2. 2016SPICE: Semantic Propositional Image Caption Evaluationcited by 820
  3. 2018Summarizing Videos with Attentioncited by 69
  4. 2018V3C - a Research Video Collectioncited by 12
  5. 2017Evaluation of Automatic Video Captioning Using Direct Assessmentcited by 7

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Citing papers per year: 2021: 2; 2022: 5; 2023: 2; 2024: 6; 2025: 1.

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  1. 2023MovieChat: From Dense Token to Sparse Memory for Long Video Understandingcited by 536
  2. 2024MovieChat+: Question-aware Sparse Memory for Long Video Question Answeringcited by 73
  3. 2024WTS: A Pedestrian-Centric Traffic Video Dataset for Fine-grained Spatial-Temporal Understandingcited by 17
  4. 2022MDMMT-2: Multidomain Multimodal Transformer for Video Retrieval, One More Step Towards Generalizationcited by 10
  5. 2024ActionHub: A Large-scale Action Video Description Dataset for Zero-shot Action Recognitioncited by 8
  6. 2022Argus++: Robust Real-time Activity Detection for Unconstrained Video Streams with Overlapping Cube Proposalscited by 6
  7. 2022MMSys'22 Grand Challenge on AI-based Video Production for Soccercited by 6
  8. 2022Video Summarization Overviewcited by 6
  9. 2022BERTHA: Video Captioning Evaluation Via Transfer-Learned Human Assessmentcited by 3
  10. 2024Improving Interpretable Embeddings for Ad-hoc Video Search with Generative Captions and Multi-word Concept Bankcited by 3
  11. 2021Synchronized Audio-Visual Frames with Fractional Positional Encoding for Transformers in Video-to-Text Translationcited by 2
  12. 2024LADI v2: Multi-label Dataset and Classifiers for Low-Altitude Disaster Imagerycited by 2
4 more
  1. 2021Extended Self-Critical Pipeline for Transforming Videos to Text (TRECVID-VTT Task 2021) -- Team: MMCUniAugsburgcited by 1
  2. 2023Academic competitionscited by 0
  3. 2024Towards Multi-Task Multi-Modal Models: A Video Generative Perspectivecited by 0
  4. 2025Learning Partially-Decorrelated Common Spaces for Ad-hoc Video Searchcited by 0