5 accepted papers
Forecasting gaze behavior is an important task for understanding user intent and creating AR/VR systems that can anticipate where users will look and interact next. While prior works have addressed predicting scanpaths in static images, forecasting gaze in egocentric videos presents new challenges d
Modern perception models, particularly those designed for multisensory egocentric tasks, have achieved remarkable performance but often come with substantial computational costs. These high demands pose challenges for real-world deployment, especially in resource-constrained environments. In this pa…
Enabling autonomous language agents to drive application user interfaces (UIs) as humans do can significantly expand the capability of today’s API-based agents. Essential to this vision is the ability of agents to ground natural language commands to on-screen UI elements. Prior UI grounding approach…
Given its wide applications, there is increasing focus on generating 3D human motions from textual descriptions. Differing from the majority of previous works, which regard actions as single entities and can only generate short sequences for simple motions, we propose EMS, an elaborative motion synt…
"To avoid the time-consuming annotating and retraining cycle in applying supervised action recognition models, Zero-Shot Action Recognition (ZSAR) has become a thriving direction. ZSAR requires models to recognize actions that never appear in the training set through bridging visual features and sem…