TGIF-Action

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

5 shown of 5 papers with code (7 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.

• Lightweight Recurrent Cross-modal Encoder for Video Question Answering
  30 Jun 2023 1 repository listed
  Due to the high computational cost of the self-attention and the high dimensional data of video, they either have to settle for: 1) only training the cross-modal encoder on offline-extracted video and text features or…
• MELTR: Meta Loss Transformer for Learning to Fine-tune Video Foundation Models
  23 Mar 2023 1 repository listed Syntology ran 1 of 1 samples · 0 unverified
  Therefore, we propose MEta Loss TRansformer (MELTR), a plug-in module that automatically and non-linearly combines various loss functions to aid learning the target task via auxiliary learning.
• An Empirical Study of End-to-End Video-Language Transformers with Masked Visual Modeling
  4 Sep 2022 1 repository listed
  Masked visual modeling (MVM) has been recently proven effective for visual pre-training.
• Clover: Towards A Unified Video-Language Alignment and Fusion Model
  16 Jul 2022 1 repository listed
  We then introduce \textbf{Clover}\textemdash a Correlated Video-Language pre-training method\textemdash towards a universal Video-Language model for solving multiple video understanding tasks with neither performance…
• All in One: Exploring Unified Video-Language Pre-training
  14 Mar 2022 1 repository listed
  In this work, we for the first time introduce an end-to-end video-language model, namely \textit{all-in-one Transformer}, that embeds raw video and textual signals into joint representations using a unified backbone…

Syntology lines on 1 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.