Controlling the Quality of Distillation in Response-Based Network Compression. - Vibhas Vats; David Crandall (CoRR, 2021)

Examining the Impact of Network Architecture on Extracted Feature Quality for CBR. - David Leake; Zachary Wilkerson; Vibhas Vats; Karan Acharya; David J. Crandall (ICCBR, 2023)

Extracting Indexing Features for CBR from Deep Neural Networks: A Transfer Learning Approach. - Zachary Wilkerson; David Leake; Vibhas Vats; David Crandall (ICCBR, 2024)

GC-MVSNet: Multi-View, Multi-Scale, Geometrically-Consistent Multi-View Stereo. - Vibhas K. Vats; Sripad Joshi; David J. Crandall; Md. Alimoor Reza; Soon-Heung Jung (WACV, 2024)

Learning Case Features with Proxy-Guided Deep Neural Networks. - Vibhas Vats; Zachary Wilkerson; Hiroki Sato; David Leake; David Crandall (ICCBR, 2025)

Blending 3D Geometry and Machine Learning for Multi-View Stereopsis. - Vibhas Vats; Md. Alimoor Reza; David Crandall; Soon-Heung Jung (CoRR, 2025)

Geometric Constraints in Deep Learning Frameworks: A Survey. - Vibhas K. Vats; David Crandall (ACM Comput. Surv., 2025)