Sponsored by IARPA’s BRIAR program, GRAIL develops systems and algorithms for face and whole-body authentication at altitude and range using long-range visible imagery under challenging imaging conditions.

Sponsored by DARPA’s Medifor program, DiSPARITY develops deep learning algorithms for identifying digital, physical, and semantic image and video manipulations. Image manipulations include image splicing, copy-move, and image repurposing. DiSPARITY also develops robust, subject-agnostic machine learning methods and systems for deepfake detection.

Sponsored by DARPA’s GARD program, LR2 develops deep learning models that are robust to adversarial attacks. Our work covers models for numerous tasks spanning different modalities, such as image classification, object detection, action recognition, object tracking, speaker identification, and automatic speech recognition.

Sponsored by DARPA’s LwLL program, CORAL develops machine learning algorithms that require significantly smaller amounts of labeled training data for computer vision tasks, such as image classification, object detection, and semantic image segmentation; and natural language processing tasks such as machine translation and named entity recognition.

Congenital adrenal hyperplasia (CAH) is a genetic disorder with serious life-long health implications. Face2CAH considers using the face as a phenotypic biomarker that can be easily used by physicians to adjust medications for CAH patients to improve their quality of life.

Sponsored by IARPA’s Odin/Thor program, BATL develops systems and algorithms resilient to presentation attacks (spoofing) of biometric authentication systems, including face, iris, and fingerprint systems.