6 papers
K9-Bench: Evaluating Multimodal LLMs on Canine-Centric Videos
Khush Attarde, Yusuf Ali, Megha Thukral +3
MLLMs have shown strong zero-shot capabilities across diverse inputs such as across images, video, audio, and text. A crucial, yet underexplored, application of these models lies i…
Fine-grained Motion Retrieval via Joint-Angle Motion Images and Token-Patch Late Interaction
Yao Zhang, Zhuchenyang Liu, Yanlan He +2
Text-motion retrieval aims to learn a semantically aligned latent space between natural language descriptions and 3D human motion skeleton sequences, enabling bidirectional search…
Encoder-Free Human Motion Understanding via Structured Motion Descriptions
Yao Zhang, Zhuchenyang Liu, Thomas Ploetz +1
The world knowledge and reasoning capabilities of text-based large language models (LLMs) are advancing rapidly, yet current approaches to human motion understanding, including mot…
Foundation Models Defining A New Era In Sensor-based Human Activity Recognition: A Survey And Outlook
Sizhen Bian, Mengxi Liu, Lala Shakti Swarup Ray +7
Sensor-based Human Activity Recognition (HAR) underpins many ubiquitous and wearable computing applications, yet current models remain limited by scarce labels, sensor heterogeneit…
Models Got Talent: Identifying High Performing Wearable Human Activity Recognition Models Without Training
Richard Goldman, Varun Komperla, Thomas Ploetz +1
A promising alternative to the computationally expensive Neural Architecture Search (NAS) involves the development of Zero Cost Proxies (ZCPs), which correlate well with trained pe…
Thou Shalt Not Prompt: Zero-Shot Human Activity Recognition in Smart Homes via Language Modeling of Sensor Data & Activities
Sourish Gunesh Dhekane, Thomas Ploetz
Developing zero-shot human activity recognition (HAR) methods is a critical direction in smart home research -- considering its impact on making HAR systems work across smart homes…