Event Segmentation

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

3 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

1 subtask in the archive's task tree.

Most implemented papers archive 2025-07-28

9 shown of 9 papers with code (23 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Generic Event Boundary Detection: A Benchmark for Event Segmentation
  26 Jan 2021 2 repositories listed
  This paper presents a novel task together with a new benchmark for detecting generic, taxonomy-free event boundaries that segment a whole video into chunks.
• Memory Storyboard: Leveraging Temporal Segmentation for Streaming Self-Supervised Learning from Egocentric Videos
  21 Jan 2025 1 repository listed
  To accommodate efficient temporal segmentation, we propose a two-tier memory hierarchy: the recent past is stored in a short-term memory, and the storyboard temporal segments are then transferred to a long-term memory.
• Human-like Episodic Memory for Infinite Context LLMs
  12 Jul 2024 1 repository listed Syntology ran 10 of 13 samples · 3 unverified
  Large language models (LLMs) have shown remarkable capabilities, but still struggle with processing extensive contexts, limiting their ability to maintain coherence and accuracy over long sequences.
• Developing hierarchical anticipations via neural network-based event segmentation
  4 Jun 2022 1 repository listed
  Humans can make predictions on various time scales and hierarchical levels.
• CoSeg: Cognitively Inspired Unsupervised Generic Event Segmentation
  30 Sep 2021 1 repository listed
  Unlike the mainstream clustering-based methods, our framework exploits a transformer-based feature reconstruction scheme to detect event boundary by reconstruction errors.
• Generic Event Boundary Detection Challenge at CVPR 2021 Technical Report: Cascaded Temporal Attention Network (CASTANET)
  1 Jul 2021 1 repository listed
  In this work, we design a Cascaded Temporal Attention Network (CASTANET) for GEBD, which is formed by three parts, the backbone network, the temporal attention module, and the classification module.
• Enhancing temporal segmentation by nonlocal self-similarity
  14 Jun 2019 1 repository listed
  Temporal segmentation of untrimmed videos and photo-streams is currently an active area of research in computer vision and image processing.
• Event-Based Motion Segmentation by Motion Compensation
  2 Apr 2019 1 repository listed
  In contrast to traditional cameras, whose pixels have a common exposure time, event-based cameras are novel bio-inspired sensors whose pixels work independently and asynchronously output intensity changes (called…
• A Perceptual Prediction Framework for Self Supervised Event Segmentation
  12 Nov 2018 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  We also show that the proposed approach is able to learn highly discriminative features that help improve action recognition when used in a representation learning paradigm.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.