4 citations · 4 across the 3 of their papers we have counts for
5 papers · 1 filter
VideoFlexTok: Flexible-Length Coarse-to-Fine Video Tokenization
Andrei Atanov, Jesse Allardice, Roman Bachmann +6
Visual tokenizers map high-dimensional raw pixels into a compressed representation for downstream modeling. Beyond compression, tokenizers dictate what information is preserved and…
SO-Bench: A Structural Output Evaluation of Multimodal LLMs
Di Feng, Kaixin Ma, Feng Nan +9
Multimodal large language models (MLLMs) are increasingly deployed in real-world, agentic settings where outputs must not only be correct, but also conform to predefined data schem…
MM-Spatial: Exploring 3D Spatial Understanding in Multimodal LLMs
Erik Daxberger, Nina Wenzel, David Griffiths +8
Multimodal large language models (MLLMs) excel at 2D visual understanding but remain limited in their ability to reason about 3D space. In this work, we leverage large-scale high-q…
Cubify Anything: Scaling Indoor 3D Object Detection
Justin Lazarow, David Griffiths, Gefen Kohavi +2
We consider indoor 3D object detection with respect to a single RGB(-D) frame acquired from a commodity handheld device. We seek to significantly advance the status quo with respec…
4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities
Roman Bachmann, Oğuzhan Fatih Kar, David Mizrahi +6
Current multimodal and multitask foundation models like 4M or UnifiedIO show promising results, but in practice their out-of-the-box abilities to accept diverse inputs and perform…