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20142026
most citedLearning from Synthetic Humans

978 citations · 4.5k across the 70 of their papers we have counts for

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Showing 2023 · cs.CVShow all

5 papers · 2 filters

cs.CV2023

GenHowTo: Learning to Generate Actions and State Transformations from Instructional Videos

Tomáš Souček, Dima Damen, Michael Wray +2

We address the task of generating temporally consistent and physically plausible images of actions and object state transformations. Given an input image and a text prompt describi…

cs.CV2023★ 2 cited

VidChapters-7M: Video Chapters at Scale

Antoine Yang, Arsha Nagrani, Ivan Laptev +2

Segmenting long videos into chapters enables users to quickly navigate to the information of their interest. This important topic has been understudied due to the lack of publicly…

cs.CV2023

Object Goal Navigation with Recursive Implicit Maps

Shizhe Chen, Thomas Chabal, Ivan Laptev +1

Object goal navigation aims to navigate an agent to locations of a given object category in unseen environments. Classical methods explicitly build maps of environments and require…

cs.CV2023★ 1 cited

gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstruction

Zerui Chen, Shizhe Chen, Cordelia Schmid +1

Signed distance functions (SDFs) is an attractive framework that has recently shown promising results for 3D shape reconstruction from images. SDFs seamlessly generalize to differe…

cs.CV2023★ 15 cited

Vid2Seq: Large-Scale Pretraining of a Visual Language Model for Dense Video Captioning

Antoine Yang, Arsha Nagrani, Paul Hongsuck Seo +5

In this work, we introduce Vid2Seq, a multi-modal single-stage dense event captioning model pretrained on narrated videos which are readily-available at scale. The Vid2Seq architec…