1 citations · 2 across the 2 of their papers we have counts for
3 papers · 1 filter
Seeing Faces in Things: A Model and Dataset for Pareidolia
Mark Hamilton, Simon Stent, Vasha DuTell +4
The human visual system is well-tuned to detect faces of all shapes and sizes. While this brings obvious survival advantages, such as a better chance of spotting unknown predators…
Separating the "Chirp" from the "Chat": Self-supervised Visual Grounding of Sound and Language
Mark Hamilton, Andrew Zisserman, John R. Hershey +1
We present DenseAV, a novel dual encoder grounding architecture that learns high-resolution, semantically meaningful, and audio-visually aligned features solely through watching vi…
FeatUp: A Model-Agnostic Framework for Features at Any Resolution
Stephanie Fu, Mark Hamilton, Laura Brandt +3
Deep features are a cornerstone of computer vision research, capturing image semantics and enabling the community to solve downstream tasks even in the zero- or few-shot regime. Ho…