5 papers · 1 filter
Face, Whole-Person, and Object Classification in a Unified Space Via The Interleaved Multi-Domain Identity Curriculum
Thomas M Metz, Matthew Q Hill, Alice J O'Toole
Vision foundation models can perform generalized object classification in zero-shot mode, and face/person recognition when they are fine-tuned. However, fine-tuned models suffer fr…
Not All Starting Points Are Equal: Pre-trained Priors and Their Outsized Impact on Person Identification
Thomas M. Metz, Matthew Q. Hill, Alice J. O'Toole
Recent years have seen an explosion of diverse general purpose pre-training methodologies for computer vision. However, the impact that these pre-training methodologies have on per…
Dissecting Human Body Representations in Deep Networks Trained for Person Identification
Thomas M Metz, Matthew Q Hill, Blake Myers +3
Long-term body identification algorithms have emerged recently with the increased availability of high-quality training data. We seek to fill knowledge gaps about these models by a…
Unconstrained Body Recognition at Altitude and Range: Comparing Four Approaches
Blake A Myers, Matthew Q Hill, Veda Nandan Gandi +2
This study presents an investigation of four distinct approaches to long-term person identification using body shape. Unlike short-term re-identification systems that rely on tempo…
Recognizing People by Body Shape Using Deep Networks of Images and Words
Blake A. Myers, Lucas Jaggernauth, Thomas M. Metz +4
Common and important applications of person identification occur at distances and viewpoints in which the face is not visible or is not sufficiently resolved to be useful. We exami…