Program

Monday, June 19, 2023 (all times are local, i.e., Pacific Time)

09:00—09:15: Welcome and Workshop Introduction

09:15—10:15: Keynote 1 (45 min+ 15 min Q&A)  VIDEO

Laura Leal-Taixé: Multiple object tracking with graphs - from classical to learned

10:15—10:45: Poster Session/ Morning Coffee

10:45—11:15: Oral 1 (20 min+10 min Q&A)

GPr-Net: Geometric Prototypical Network for Point Cloud Few-Shot Learning. Tejas Anvekar (KLE Technological University)*; Dena Bazazian (University of Plymouth) VIDEO

11:15—12:15: Keynote 2 (45 min+ 15 min Q&A)  VIDEO

Yifan Wang: Geometric structures and why (and how) to use them in deep models?

12:15—13:30: Lunch Break

13:30—14:30: Keynote 3 (45 min+ 15 min Q&A)

Theodore Kim: Is Synthetic Training Data A Bad Idea?

14:30—15:00: Oral 2 (20 min+10 min Q&A)

GenSim: Unsupervised Generic Garment Simulator. Lokender Tiwari (TCS Research)*; Brojeshwar Bhowmick (Tata Consultancy Services); Sanjana Sinha (TCS) VIDEO

15:00– 15:30: Poster Session/ Afternoon Coffee

15:30—16:00: Oral 3 (20 min+10 min Q&A)

Improving Shape Awareness and Interpretability in Deep Networks Using Geometric Moments. Rajhans Singh (Arizona State University)*; Ankita Shukla (ASU); Pavan Turaga (Arizona State University) SLIDES

16:00—16:15: Challenge overview

16:15—16:45: Open Discussion

16:45—17:00: Closing Remarks