Pith. sign in

REVIEW 6 cited by

A Short Note on the Kinetics-700-2020 Human Action Dataset

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2010.10864 v1 pith:WZSWIOMF submitted 2020-10-21 cs.CV cs.LG

Lucas Smaira (DeepMind) , João Carreira (DeepMind) , Eric Noland (DeepMind) , Ellen Clancy (DeepMind) , Amy Wu (DeepMind) , Andrew Zisserman (DeepMind) This is my paper
classification cs.CVcs.LG
keywords datasetactionhumanbaselinechangesclassesclipscomprehensive
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

We describe the 2020 edition of the DeepMind Kinetics human action dataset, which replenishes and extends the Kinetics-700 dataset. In this new version, there are at least 700 video clips from different YouTube videos for each of the 700 classes. This paper details the changes introduced for this new release of the dataset and includes a comprehensive set of statistics as well as baseline results using the I3D network.

Discussion (0). Sign in to comment.

Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Flamingo: a Visual Language Model for Few-Shot Learning

    cs.CV 2022-04 unverdicted novelty 7.0 of 10

    Flamingo models reach new state-of-the-art few-shot results on image and video tasks by bridging frozen vision and language models with cross-attention layers trained on interleaved web-scale data.

  2. Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

    cs.CV 2022-04 unverdicted novelty 7.0 of 10

    Socratic Models compose zero-shot multimodal reasoning by prompting pretrained language and vision models to exchange information and enable new capabilities without finetuning.

  3. Perceiver IO: A General Architecture for Structured Inputs & Outputs

    cs.LG 2021-07 unverdicted novelty 7.0 of 10

    Perceiver IO is a general architecture that processes arbitrary structured inputs and outputs with linear scaling and achieves strong results on GLUE, Sintel optical flow, multi-task reasoning, and StarCraft II withou...

  4. CoCa: Contrastive Captioners are Image-Text Foundation Models

    cs.CV 2022-05 accept novelty 6.0 of 10

    CoCa unifies contrastive and generative pretraining in one image-text model to reach 86.3% zero-shot ImageNet accuracy and new state-of-the-art results on multiple downstream benchmarks.

  5. From Codebooks to VLMs: Evaluating Automated Visual Discourse Analysis for Climate Change on Social Media

    cs.CV 2026-04 unverdicted novelty 5.0 of 10

    VLMs recover reliable population-level trends in climate change visual discourse on social media even when per-image accuracy is only moderate.

  6. Planner-Refiner: Dynamic Space-Time Refinement for Vision-Language Alignment in Videos

    cs.CV 2025-08 unverdicted novelty 5.0 of 10

    Planner-Refiner decomposes complex video-language prompts into short chains and refines visual token attention across space and time, claiming state-of-the-art results on two alignment tasks.

Pith tools