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The human language is one of the most natural interfaces for humans to interact with robots. This paper presents a robot system that retrieves everyday objects with unconstrained natural language descriptions. A core issue for the system is…

Robotics · Computer Science 2017-07-19 Mohit Shridhar , David Hsu

Understanding natural-language references to objects in dynamic 3D driving scenes is essential for interactive autonomous systems. In practice, many referring expressions describe targets through recent motion or short-term interactions,…

Computer Vision and Pattern Recognition · Computer Science 2025-12-29 Jiahong Yu , Ziqi Wang , Hailiang Zhao , Wei Zhai , Xueqiang Yan , Shuiguang Deng

While current multimodal models can answer questions based on 2D images, they lack intrinsic 3D object perception, limiting their ability to comprehend spatial relationships and depth cues in 3D scenes. In this work, we propose N3D-VLM, a…

Computer Vision and Pattern Recognition · Computer Science 2025-12-19 Yuxin Wang , Lei Ke , Boqiang Zhang , Tianyuan Qu , Hanxun Yu , Zhenpeng Huang , Meng Yu , Dan Xu , Dong Yu

Unsupervised representation learning techniques, such as learning word embeddings, have had a significant impact on the field of natural language processing. Similar representation learning techniques have not yet become commonplace in the…

Computer Vision and Pattern Recognition · Computer Science 2021-02-09 Joël Bachmann , Kenneth Blomqvist , Julian Förster , Roland Siegwart

Grounding language in the physical world requires AI systems to interpret references that emerge dynamically during conversation. While current vision-language models (VLMs) excel at static image tasks, they struggle to resolve ambiguous…

Computer Vision and Pattern Recognition · Computer Science 2026-05-22 Anna Deichler , Jim O'Regan , Fethiye Irmak Dogan , Lubos Marcinek , Anna Klezovich , Iolanda Leite , Jonas Beskow

Recent advances in large vision-language models (VLMs) have shown significant promise for 3D scene understanding. Existing VLM-based approaches typically align 3D scene features with the VLM's embedding space. However, this implicit…

Computer Vision and Pattern Recognition · Computer Science 2025-12-01 Chen Li , Eric Peh , Basura Fernando

A metric-accurate semantic 3D representation is essential for many robotic tasks. This work proposes a simple, yet powerful, way to integrate the 2D embeddings of a Vision-Language Model in a metric-accurate 3D representation at real-time.…

Robotics · Computer Science 2025-08-11 Christian Rauch , Björn Ellensohn , Linus Nwankwo , Vedant Dave , Elmar Rueckert

Language grounding is an active field aiming at enriching textual representations with visual information. Generally, textual and visual elements are embedded in the same representation space, which implicitly assumes a one-to-one…

Computation and Language · Computer Science 2020-02-10 Patrick Bordes , Eloi Zablocki , Laure Soulier , Benjamin Piwowarski , Patrick Gallinari

Visual grounding is a task to locate the target indicated by a natural language expression. Existing methods extend the generic object detection framework to this problem. They base the visual grounding on the features from pre-generated…

Computer Vision and Pattern Recognition · Computer Science 2022-06-09 Li Yang , Yan Xu , Chunfeng Yuan , Wei Liu , Bing Li , Weiming Hu

3-Dimensional Embodied Reference Understanding (3D-ERU) combines a language description and an accompanying pointing gesture to identify the most relevant target object in a 3D scene. Although prior work has explored pure language-based 3D…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Atharv Mahesh Mane , Dulanga Weerakoon , Vigneshwaran Subbaraju , Sougata Sen , Sanjay E. Sarma , Archan Misra

Currently, utilizing large language models to understand the 3D world is becoming popular. Yet existing 3D-aware LLMs act as black boxes: they output bounding boxes or textual answers without revealing how those decisions are made, and they…

Computer Vision and Pattern Recognition · Computer Science 2025-06-24 Zhihao Yuan , Shuyi Jiang , Chun-Mei Feng , Yaolun Zhang , Shuguang Cui , Zhen Li , Na Zhao

One major goal of vision is to infer physical models of objects, surfaces, and their layout from sensors. In this paper, we aim to interpret indoor scenes from one RGBD image. Our representation encodes the layout of orthogonal walls and…

Computer Vision and Pattern Recognition · Computer Science 2018-11-15 Chuhang Zou , Ruiqi Guo , Zhizhong Li , Derek Hoiem

Precisely perceiving the geometric and semantic properties of real-world 3D objects is crucial for the continued evolution of augmented reality and robotic applications. To this end, we present Foundation Model Embedded Gaussian Splatting…

Computer Vision and Pattern Recognition · Computer Science 2024-05-07 Xingxing Zuo , Pouya Samangouei , Yunwen Zhou , Yan Di , Mingyang Li

3D visual grounding (3DVG) involves localizing entities in a 3D scene referred to by natural language text. Such models are useful for embodied AI and scene retrieval applications, which involve searching for objects or patterns using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-09 Austin T. Wang , ZeMing Gong , Angel X. Chang

As robots become more ubiquitous and capable, it becomes ever more important to enable untrained users to easily interact with them. Recently, this has led to study of the language grounding problem, where the goal is to extract…

Computation and Language · Computer Science 2012-07-03 Cynthia Matuszek , Nicholas FitzGerald , Luke Zettlemoyer , Liefeng Bo , Dieter Fox

The emergence of neural representations has revolutionized our means for digitally viewing a wide range of 3D scenes, enabling the synthesis of photorealistic images rendered from novel views. Recently, several techniques have been proposed…

Computer Vision and Pattern Recognition · Computer Science 2025-02-14 Gal Fiebelman , Tamir Cohen , Ayellet Morgenstern , Peter Hedman , Hadar Averbuch-Elor

A core problem of Embodied AI is to learn object manipulation from observation, as humans do. To achieve this, it is important to localize 3D object affordance areas through observation such as images (3D affordance grounding) and…

Computer Vision and Pattern Recognition · Computer Science 2026-04-02 Xinhang Wan , Dongqiang Gou , Xinwang Liu , En Zhu , Xuming He

Humans effortlessly "program" one another by communicating goals and desires in natural language. In contrast, humans program robotic behaviours by indicating desired object locations and poses to be achieved, by providing RGB images of…

Computer Vision and Pattern Recognition · Computer Science 2018-05-01 Hsiao-Yu Fish Tung , Adam W. Harley , Liang-Kang Huang , Katerina Fragkiadaki

Grounded video description (GVD) encourages captioning models to attend to appropriate video regions (e.g., objects) dynamically and generate a description. Such a setting can help explain the decisions of captioning models and prevents the…

Computer Vision and Pattern Recognition · Computer Science 2021-12-03 Wenqiao Zhang , Xin Eric Wang , Siliang Tang , Haizhou Shi , Haocheng Shi , Jun Xiao , Yueting Zhuang , William Yang Wang

Grounding referring expressions in RGBD image has been an emerging field. We present a novel task of 3D visual grounding in single-view RGBD image where the referred objects are often only partially scanned due to occlusion. In contrast to…

Computer Vision and Pattern Recognition · Computer Science 2021-03-18 Haolin Liu , Anran Lin , Xiaoguang Han , Lei Yang , Yizhou Yu , Shuguang Cui