4 papers
End-to-End Training for Unified Tokenization and Latent Denoising
Shivam Duggal, Xingjian Bai, Zongze Wu +5
Latent diffusion models (LDMs) enable high-fidelity synthesis by operating in learned latent spaces. However, training state-of-the-art LDMs requires complex staging: a tokenizer m…
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…
Eval3D: Interpretable and Fine-grained Evaluation for 3D Generation
Shivam Duggal, Yushi Hu, Oscar Michel +7
Despite the unprecedented progress in the field of 3D generation, current systems still often fail to produce high-quality 3D assets that are visually appealing and geometrically a…
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…