Workshop Program for Saturday, December 10
Saturday Morning Session: 7:30am – 10:30am7:30am – Interclass transfer for object recognition: overview and workshop goals (A. Ferencz)
7:40am – Interclass transfer as an underlying factor of human object recognition (M. Fink and S. Ullman)
8:10am – An alternative to modeling appearance: Modeling relative appearance (E. Learned-Miller and J. Weinman)
8:40am – Semi-supervised learning of distance functions, using equivalence constraints (T. Hertz and D. Weinshall)
9:10am – Coffee Break
9:30am – Transferring information using Bayesian priors on object categories (R. Fergus and L. Fei-Fei)
10:00am – Learning Shared Parts using Dirichlet Processes (E. Sudderth, A. Torralba and W. Freeman)
Saturday Afternoon Session: 3:30pm – 6:30pm
3:30am – Learning domain structures (C. Kemp and J. Tenenbaum)
4:00am – Combining generative models and Fisher kernels for object recognition (A. D. Holub, M. Welling and P. Perona)
4:30am – Pattern Recognition from One Example (F. Fleuret and G. Blanchard)
4:50am – Coffee Break
5:00am – Building a classification cascade for visual identification from one example (A. Ferencz, E. Learned-Miller and J. Malik)
5:20am – Fast visual object identification and categorization (M. Grabner, H. Grabner and H. Bischof)
5:50pm – Future challenges in applying interclass transfer for object recognition(T. Darrell, J. Malik, K. Murphy, P. Perona)
6:20pm – Final Discussion and Summary
Interclass Transfer: why learning to recognize many objects is easier than learning to recognize just one
