2 citations · 3 across the 5 of their papers we have counts for
8 papers
RGraph-Eval: Task-Grounded Scene Graphs for Evaluating Robot Video Generation
Aleksandr Lazarev, Sofia Zimina, Roman Kuznetsov +3
Generated robot videos can look convincing while depicting the wrong interaction: a different object is moved, a grasp disappears, or a placement ends outside its destination. We i…
Omni-Woodpecker: Hallucination Correction via Evidence-Prior Rebalancing for Omni LLMs
Zijian Liu, Chaoyou Fu, Yan Yang +2
Recent Omni LLMs (OLLMs) have demonstrated remarkable capabilities in joint audio-visual reasoning, yet cross-modal hallucinations remain a major challenge. Existing mitigation met…
FocusGraph: Graph-Structured Frame Selection for Embodied Long Video Question Answering
Tatiana Zemskova, Solomon Andryushenko, Ilya Obrubov +4
Understanding long videos is crucial for embodied intelligent agents, as their performance depends on effectively accumulating and using long-horizon perceptual memories. Multimoda…
OVSegDT: Segmenting Transformer for Open-Vocabulary Object Goal Navigation
Tatiana Zemskova, Aleksei Staroverov, Dmitry Yudin +1
Open-vocabulary Object Goal Navigation requires an embodied agent to reach objects described by free-form language, including categories never seen during training. Existing end-to…
3DGraphLLM: Combining Semantic Graphs and Large Language Models for 3D Scene Understanding
Tatiana Zemskova, Dmitry Yudin
A 3D scene graph represents a compact scene model by capturing both the objects present and the semantic relationships between them, making it a promising structure for robotic app…
Beyond Bare Queries: Open-Vocabulary Object Grounding with 3D Scene Graph
Sergey Linok, Tatiana Zemskova, Svetlana Ladanova +4
Locating objects described in natural language presents a significant challenge for autonomous agents. Existing CLIP-based open-vocabulary methods successfully perform 3D object gr…
Interactive Semantic Map Representation for Skill-based Visual Object Navigation
Tatiana Zemskova, Aleksei Staroverov, Kirill Muravyev +2
Visual object navigation using learning methods is one of the key tasks in mobile robotics. This paper introduces a new representation of a scene semantic map formed during the emb…
SegmATRon: Embodied Adaptive Semantic Segmentation for Indoor Environment
Tatiana Zemskova, Margarita Kichik, Dmitry Yudin +2
This paper presents an adaptive transformer model named SegmATRon for embodied image semantic segmentation. Its distinctive feature is the adaptation of model weights during infere…