Papers › Multi-modal Transformer for Video Retrieval

Multi-modal Transformer for Video Retrieval

21 Jul 2020ECCV 2020 8arXiv:2007.10639archive 2025-07-28

Valentin Gabeur, Chen Sun, Karteek Alahari, Cordelia Schmid

The task of retrieving video content relevant to natural language queries plays a critical role in effectively handling internet-scale datasets. Most of the existing methods for this caption-to-video retrieval problem do not fully exploit cross-modal cues present in video. Furthermore, they aggregate per-frame visual features with limited or no temporal information. In this paper, we present a multi-modal transformer to jointly encode the different modalities in video, which allows each of them to attend to the others. The transformer architecture is also leveraged to encode and model the temporal information. On the natural language side, we investigate the best practices to jointly optimize the language embedding together with the multi-modal transformer. This novel framework allows us to establish state-of-the-art results for video retrieval on three datasets. More details are available at http://thoth.inrialpes.fr/research/MMT.

PaperPDFConference PDFCodeCode Syntology ran

In Syntology Open this paper in Syntology's Atlas, the map of the papers in Syntology's graph and their citations.

For agents, Syntology's MCP tool lists every function and class Syntology harvested from this paper and whether it ran (how to connect): get_harvested_code_for_paper(arxiv_id="2007.10639")

Code

Syntology Ran 1 of 7 code samples harvested from 1 repository linked to this paper; 6 have no recorded run. Of those that ran: 1 ran · our draft was wrong.

By repository: community (archive-listed): 7 samples from 1 repository, 1 ran. The run record, sample by sample. “Ran” means executed on a synthesized input, not that the code is correct or reproduces the paper.

gabeur/mmt mentioned on GitHubpytorchApache-2.0 report

Repository list and official/mentioned flags are the archive's, frozen 2025-07-28. Reachability, where shown, is from one Syntology probe window (2026-09-16 to 2026-09-18); repositories not probed show nothing. GitHub stars are not tracked.

Code Syntology ran Syntology

7 samples harvested; 1 ran; 0 honoured the contract we drafted; 6 have no recorded run. Read from Syntology's graph 2026-09-24; that is when this build read the record, not when the samples ran.

1ran · our draft was wrong
6unverified

Licence: 0 of the 7 samples are pointer only, meaning Syntology does not serve that copy's text. This page shows no code text for any sample; each one links to its file in the repository.

Harvested from gabeur/mmt. “Ran” means the sample executed on a synthesized input. It does not mean the output is correct, and nothing here reproduces the paper's results. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code.

Each sample ends with its code_sha256, Syntology's identity for that exact code. An agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

Repository labels, per sample. official repository: The archive marks this repository official for the paper. named in the paper: The archive records that the paper mentions this repository; it is not marked official. community (archive-listed): In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper. found in paper text by Syntology: Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted. community: Not in the archive's code links for this paper; a community repository Syntology harvested. Samples from a repository marked official are listed first. Licence labels name the repository's licence as recorded at harvest. “Pointer only” means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence label for the reason. File links open the file on GitHub at the default branch, which may have changed since the harvest.

swish gabeur/mmt/model/bert.py community (archive-listed) ran · our draft was wrong fingerprinted Apache-2.0 (permissive) · 0f786c407fb1ee4c · report
cols2metrics gabeur/mmt/model/metric.py community (archive-listed) unverified Apache-2.0 (permissive) · bd78c55f13b78ce3 · report
gelu gabeur/mmt/model/bert.py community (archive-listed) unverified Apache-2.0 (permissive) · 2fd42cf688d23870 · report
get_clean_word gabeur/mmt/base/base_dataset.py community (archive-listed) unverified Apache-2.0 (permissive) · 3910f45c24ea70d4 · report
is_end_of_sentence gabeur/mmt/base/base_dataset.py community (archive-listed) unverified Apache-2.0 (permissive) · 1f25d43573a02940 · report
sharded_cross_view_inner_product gabeur/mmt/model/model.py community (archive-listed) unverified Apache-2.0 (permissive) · d7cd977eb21d3ff8 · report
v2t_metrics gabeur/mmt/model/metric.py community (archive-listed) unverified Apache-2.0 (permissive) · 79bc20d6b4080f0b · report

Tasks

Natural Language QueriesRetrievalVideo RetrievalZero-Shot Video Retrieval

Results from the paper archive 2025-07-28

TaskDatasetModelMetricValueRank at snapshotLeaderboardReport
Video Retrieval ActivityNet MMT-Pretrained text-to-video Mean Rank 16 #27 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT-Pretrained text-to-video Median Rank 3.3 #27 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT-Pretrained text-to-video R@1 28.7 #27 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT-Pretrained text-to-video R@5 61.4 #27 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT-Pretrained text-to-video R@50 94.5 #27 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT text-to-video Mean Rank 20.8 #30 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT text-to-video Median Rank 5 #30 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT text-to-video R@1 22.7 #30 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT text-to-video R@5 54.2 #30 of 31 Archive leaderboard report
Video Retrieval ActivityNet MMT text-to-video R@50 93.2 #30 of 31 Archive leaderboard report
Video Retrieval LSMDC MMT-Pretrained text-to-video Median Rank 19.3 #29 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT-Pretrained text-to-video R@1 13.5 #29 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT-Pretrained text-to-video R@10 40.1 #29 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT-Pretrained text-to-video R@5 29.9 #29 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT text-to-video Median Rank 21 #30 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT text-to-video R@1 13.2 #30 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT text-to-video R@10 38.8 #30 of 38 Archive leaderboard report
Video Retrieval LSMDC MMT text-to-video R@5 29.2 #30 of 38 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT-Pretrained text-to-video Mean Rank 24.0 #53 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT-Pretrained text-to-video Median Rank 4 #53 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT-Pretrained text-to-video R@1 26.6 #53 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT-Pretrained text-to-video R@10 69.6 #53 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT-Pretrained text-to-video R@5 57.1 #53 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT text-to-video Mean Rank 26.7 #55 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT text-to-video Median Rank 4 #55 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT text-to-video R@1 24.6 #55 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT text-to-video R@10 67.1 #55 of 63 Archive leaderboard report
Video Retrieval MSR-VTT-1kA MMT text-to-video R@5 54.0 #55 of 63 Archive leaderboard report
Zero-Shot Video Retrieval MSR-VTT MMT text-to-video Mean Rank 148.1 #40 of 41 Archive leaderboard report
Zero-Shot Video Retrieval MSR-VTT MMT text-to-video Median Rank 66 #40 of 41 Archive leaderboard report
Zero-Shot Video Retrieval MSR-VTT MMT text-to-video R@5 14.4 #40 of 41 Archive leaderboard report

Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections