activity
20242026
most citedSlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

4 citations · 4 across the 4 of their papers we have counts for

collaborators

5 papers

cs.RO2026

: An Open Foundation Model Towards Universal Humanoid Loco-Manipulation

Songlin Wei, Hongyi Jing, Boqian Li +12

We introduce (Psi-Zero), an open foundation model to address challenging humanoid loco-manipulation tasks. While existing approaches often attempt to address this fundamental…

cs.CV2025

Rooms from Motion: Un-posed Indoor 3D Object Detection as Localization and Mapping

Justin Lazarow, Kai Kang, Afshin Dehghan

We revisit scene-level 3D object detection as the output of an object-centric framework capable of both localization and mapping using 3D oriented boxes as the underlying geometric…

cs.CV2025

SlowFast-LLaVA-1.5: A Family of Token-Efficient Video Large Language Models for Long-Form Video Understanding

Mingze Xu, Mingfei Gao, Shiyu Li +7

We introduce SlowFast-LLaVA-1.5 (abbreviated as SF-LLaVA-1.5), a family of video large language models (LLMs) offering a token-efficient solution for long-form video understanding.…

cs.CV2025

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…

cs.CV2024★ 4 cited

SlowFast-LLaVA: A Strong Training-Free Baseline for Video Large Language Models

Mingze Xu, Mingfei Gao, Zhe Gan +5

We propose SlowFast-LLaVA (or SF-LLaVA for short), a training-free video large language model (LLM) that can jointly capture detailed spatial semantics and long-range temporal cont…