Humans describe the physical world using natural language to refer to specific 3D locations
based on a vast range of properties: visual appearance, semantics, abstract associations, or …

Humans live in a 3D world and commonly use natural language to interact with a 3D scene.
Modeling a 3D language field to support open-ended language queries in 3D has gained …

Benchmarks for large multimodal language models (MLMs) now serve to simultaneously
assess the general capabilities of models instead of evaluating for a specific capability. As a …

Large-scale pre-trained Vision & Language (VL) models have shown remarkable
performance in many applications, enabling replacing a fixed set of supported classes with …

Grasp detection is a persistent and intricate challenge with various industrial applications.
Recently many methods and datasets have been proposed to tackle the grasp detection …

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 …

This study investigates unsupervised anomaly action recognition, which identifies video-
level abnormal-human-behavior events in an unsupervised manner without abnormal …

Abstract While Visual Question Answering (VQA) has progressed rapidly, previous works
raise concerns about robustness of current VQA models. In this work, we study the …

Almost all previous text-to-video retrieval works assume that videos are pre-trimmed with
short durations. However, in practice, videos are generally untrimmed containing much …

Earth vision research typically focuses on extracting geospatial object locations and
categories but neglects the exploration of relations between objects and comprehensive …