7 citations · 7 across the 6 of their papers we have counts for
14 papers · 1 filter
Let's Split Up: Zero-Shot Classifier Edits for Fine-Grained Video Understanding
Kaiting Liu, Hazel Doughty
Video recognition models are typically trained on fixed taxonomies which are often too coarse, collapsing distinctions in object, manner or outcome under a single label. As tasks a…
Segmenting Collision Sound Sources in Egocentric Videos
Kranti Kumar Parida, Omar Emara, Hazel Doughty +1
Humans excel at multisensory perception and can often recognise object properties from the sound of their interactions. Inspired by this, we propose the novel task of Collision Sou…
SEVERE++: Evaluating Benchmark Sensitivity in Generalization of Video Representation Learning
Fida Mohammad Thoker, Letian Jiang, Chen Zhao +4
Continued advances in self-supervised learning have led to significant progress in video representation learning, offering a scalable alternative to supervised approaches by removi…
HD-EPIC: A Highly-Detailed Egocentric Video Dataset
Toby Perrett, Ahmad Darkhalil, Saptarshi Sinha +16
We present a validation dataset of newly-collected kitchen-based egocentric videos, manually annotated with highly detailed and interconnected ground-truth labels covering: recipe…
LocoMotion: Learning Motion-Focused Video-Language Representations
Hazel Doughty, Fida Mohammad Thoker, Cees G. M. Snoek
This paper strives for motion-focused video-language representations. Existing methods to learn video-language representations use spatial-focused data, where identifying the objec…
Beyond Coarse-Grained Matching in Video-Text Retrieval
Aozhu Chen, Hazel Doughty, Xirong Li +1
Video-text retrieval has seen significant advancements, yet the ability of models to discern subtle differences in captions still requires verification. In this paper, we introduce…