activity
20182026
most citedAdversarial Background-Aware Loss for Weakly-supervised Temporal Activity Localization

8 citations · 12 across the 16 of their papers we have counts for

collaborators
Showing 2023Show all

5 papers · 1 filter

cs.CV2023

Action Scene Graphs for Long-Form Understanding of Egocentric Videos

Ivan Rodin, Antonino Furnari, Kyle Min +2

We present Egocentric Action Scene Graphs (EASGs), a new representation for long-form understanding of egocentric videos. EASGs extend standard manually-annotated representations o…

cs.CV2023

STHG: Spatial-Temporal Heterogeneous Graph Learning for Advanced Audio-Visual Diarization

Kyle Min

This report introduces our novel method named STHG for the Audio-Visual Diarization task of the Ego4D Challenge 2023. Our key innovation is that we model all the speakers in a vide…

cs.CV2023

WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models

Changhoon Kim, Kyle Min, Maitreya Patel +2

The rapid advancement of generative models, facilitating the creation of hyper-realistic images from textual descriptions, has concurrently escalated critical societal concerns suc…

cs.CV20233 cited

SViTT: Temporal Learning of Sparse Video-Text Transformers

Yi Li, Kyle Min, Subarna Tripathi +1

Do video-text transformers learn to model temporal relationships across frames? Despite their immense capacity and the abundance of multimodal training data, recent work has reveal…

cs.CV2023

Unbiased Scene Graph Generation in Videos

Sayak Nag, Kyle Min, Subarna Tripathi +1

The task of dynamic scene graph generation (SGG) from videos is complicated and challenging due to the inherent dynamics of a scene, temporal fluctuation of model predictions, and…