5 papers
Separating Knowledge and Perception with Procedural Data
Adrián RodrÃguez-Muñoz, Manel Baradad, Phillip Isola +1
We train representation models with procedural data only, and apply them on visual similarity, classification, and semantic segmentation tasks without further training by using vis…
Single-pass Adaptive Image Tokenization for Minimum Program Search
Shivam Duggal, Sanghyun Byun, William T. Freeman +2
According to Algorithmic Information Theory (AIT) -- Intelligent representations compress data into the shortest possible program that can reconstruct its content, exhibiting low K…
What Makes for a Good Stereoscopic Image?
Netanel Y. Tamir, Shir Amir, Ranel Itzhaky +8
With rapid advancements in virtual reality (VR) headsets, effectively measuring stereoscopic quality of experience (SQoE) has become essential for delivering immersive and comforta…
Adaptive Length Image Tokenization via Recurrent Allocation
Shivam Duggal, Phillip Isola, Antonio Torralba +1
Current vision systems typically assign fixed-length representations to images, regardless of the information content. This contrasts with human intelligence - and even large langu…
When Does Perceptual Alignment Benefit Vision Representations?
Shobhita Sundaram, Stephanie Fu, Lukas Muttenthaler +5
Humans judge perceptual similarity according to diverse visual attributes, including scene layout, subject location, and camera pose. Existing vision models understand a wide range…