Browse State-of-the-Art › Text-to-Video Generation

Text-to-Video Generation

97 papers with code · 6 benchmarks · 14 datasets archive 2025-07-28

Computer VisionNatural Language Processing

Ma grand-mère m’a raconté que quand elle était étudiante, elle avait un petit-ami. À l’âge de 18 ans, il a dû partir pour le service militaire, elle ne l’a pas attendu et elle a épousé quelqu’un d’autre. Quand ma grand-mère avait 58-59 ans, un homme (son premier amour) lui a envoyé une demande d’amis sur un réseau social, ils ont commencé à parler... En moins de six mois, ils ont décidé de se voir. Le trajet en train a duré deux jours et ils se sont finalement rencontrés. Cela fait maintenant deux ans qu’ils habitent ensemble et qu’ils nous rendent visite de temps en temps. Je réalise maintenant que leur amour l’un envers l’autre n’a jamais cessé.

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

6 leaderboard tables shown for this task, 6 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.

DatasetBest model (first row in archive order)PaperCodeSyntologyCompare
MSR-VTT (18 rows) Snap Video (512x288) Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis — — Compare
UCF-101 (10 rows) Snap Video (Zero-shot, 512x288) Snap Video: Scaled Spatiotemporal Transformers for Text-to-Video Synthesis — — Compare
EvalCrafter Text-to-Video (ECTV) Dataset (5 rows) VideoCrafter2 VideoCrafter2: Overcoming Data Limitations for High-Quality Video... code Syntology ran 14 of 21 samples · 7 unverified Compare
Kinetics (1 row) NUWA (128×128) NÜWA: Visual Synthesis Pre-training for Neural visUal World creAtion code Syntology ran 3 of 3 samples · 0 unverified Compare
Something-Something V2 (1 row) MAGVIT MAGVIT: Masked Generative Video Transformer code Syntology ran 1 of 10 samples · 9 unverified Compare
WebVid (1 row) VideoFactory Swap Attention in Spatiotemporal Diffusions for Text-to-Video Generation code — Compare

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

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

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 97 papers with code (201 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.

Syntology lines on 15 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.

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