4 accepted papers
We introduce MUSE-VL, a Unified Vision-Language Model through Semantic discrete Encoding for multimodal understanding and generation. Recently, the research community has begun exploring unified models for visual generation and understanding. However, existing vision tokenizers (e.g., VQGAN) only co…
Vision-based action segmentation is an important tool in human movement analysis. In this work, we present a novel Encoder-Decoder Graph Convolutional Network (ED-GCN) to perform auto-segmentation on two widely accepted clinical tests for human mobility and balance assessment: the "Timed-Up-and-Go"…
Cropland segmentation of satellite images is an essential basis for crop area and yield estimation tasks in the remote sensing and computer vision interdisciplinary community. Instead of common pixel-level segmentation results with salt-and-pepper effects, a parcel-level output conforming to human r…
Center of pressure (COP) is an important measurement of postural and gait control in human biomechanical studies. A vision-based estimation of COP metrics offers a way to obtain these gold-standard metrics for the detection of balance and gait problems. In this paper, we propose an end-to-end framew…