1 citations · 1 across the 8 of their papers we have counts for
10 papers
ChronoGraph: Functional 4D Scene Graphs with Vision-Language Models for Interaction Understanding and Grounded Planning
Chenyangguang Zhang, Malgorzata Gwiazda, Guanlong Jiao +5
Embodied agents must determine where to act, anticipate the resulting scene changes, and interpret observed outcomes to guide subsequent actions. This requires connecting 4D intera…
Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering
Jaewoo Jung, Hyeonseo Yu, Honggyu An +10
Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs handle single-image inputs effe…
PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding
Selim Kuzucu, Alessio Tonioni, Vasile Lup +3
Large Vision-Language Models (LVLMs) map visual inputs into dense token sequences, imposing a quadratic computational bottleneck for inference. Elastic visual-token compression add…
3D Segmentation Using Viewpoint-Dependent Spatial Relationships
Ayaka Nanri, Klara Reichard, Mert Kiray +3
Recent advances in 3D datasets and multimodal models have greatly improved natural language 3D scene understanding. However, most 3D referring segmentation methods do not explicitl…
Featurising Pixels from Dynamic 3D Scenes with Linear In-Context Learners
Nikita Araslanov, Martin Sundermeyer, Hidenobu Matsuki +2
One of the most exciting applications of vision models involve pixel-level reasoning. Despite the abundance of vision foundation models, we still lack representations that effectiv…
SSL-R1: Self-Supervised Visual Reinforcement Post-Training for Multimodal Large Language Models
Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr +2
Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of enhancing the reasoning abilities in multimodal large language models (MLLMs). Ho…
R-CoV: Region-Aware Chain-of-Verification for Alleviating Object Hallucinations in LVLMs
Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr +2
Large vision-language models (LVLMs) have demonstrated impressive performance in various multimodal understanding and reasoning tasks. However, they still struggle with object hall…
OVI-MAP:Open-Vocabulary Instance-Semantic Mapping
Zilong Deng, Federico Tombari, Marc Pollefeys +2
Incremental open-vocabulary 3D instance-semantic mapping is essential for autonomous agents operating in complex everyday environments. However, it remains challenging due to the n…
Towards Real-Time Open-Vocabulary Video Instance Segmentation
Bin Yan, Martin Sundermeyer, David Joseph Tan +2
In this paper, we address the challenge of performing open-vocabulary video instance segmentation (OV-VIS) in real-time. We analyze the computational bottlenecks of state-of-the-ar…
LayoutVLM: Differentiable Optimization of 3D Layout via Vision-Language Models
Fan-Yun Sun, Weiyu Liu, Siyi Gu +6
Spatial reasoning is a fundamental aspect of human cognition, enabling intuitive understanding and manipulation of objects in three-dimensional space. While foundation models demon…