The Helmholtz Prize

The biennial Helmholtz prize is presented by the IEEE Pattern Analysis and Machine Intelligence (PAMI) Technical Committee at each ICCV for fundamental contributions in computer vision. The award recognizes ICCV papers from ten years ago with significant impact on computer vision research. The prize is named after the 19th century physician and physicist Hermann von Helmholtz. Winners are decided by a committee appointed by the TCPAMI Awards Committee.

Beginning this year, the Awards Committee is accepting nominations for papers to be considered for the Helmholtz prize. With the continued growth of our research community, including the number of papers appearing at ICCV each year, the committee feels that opening up the process for nominations will improve the selection process and reduce the chances of missing a worthy paper. Please note that a paper does NOT need an external nomination to be considered for the award. The selection committee will still conduct its usual process, with nominated papers added to the pool under consideration. Nominations are particularly encouraged for papers where the original version first appeared at ICCV but a better-known and more commonly cited version was subsequently published in journal form, making the full impact of the ICCV paper less obvious.

Nominations should include the title of the paper with a brief explanation of any non-obvious impact. Nominations should be submitted by the deadline set by the PAMI TC Chair to pami.awards@gmail.com.

The list of previous awardees can be found here.

Previous Awardees

2023 “Action Recognition With Improved Trajectories” H. Wang and C. Schmid
2021 “ORB: An efficient alternative to SIFT or SURF” E. Rublee, V. Rabaud, K. Konolige, G. Bradski
2021 “HMDB: A large video database for human motion recognition” H. Kuehne, H. Jhuang, E. Garrote, T. Poggio, T. Serre
2021 “DTAM: Dense tracking and mapping in real-time” R. Newcombe, S. Lovegrove, A. Davison
2019 “Building Rome in a Day” S. Agarwal, N. Snavely, I. Simon, S. M. Seitz, R. Szeliski
2019 “Attribute and Simile Classifiers for Face Verification” N. Kumar, A. C. Berg, P. N. Belhumeur, S. K. Nayar
2017 “Space-time interest points” I. Laptev and T. Lindeberg
2017 “Recognizing action at a distance” A. Efros, A. Berg, G. Mori, J. Malik
2017 “Video Google: A text retrieval approach to object matching in videos” J. Sivic and A. Zisserman
2017 “Recognising panoramas” M. Brown and D. Lowe
2017 “Discovering objects and their location in images” J. Sivic, B. Russell, A. Efros, A. Zisserman, and W. Freeman
2017 “The pyramid match kernel: Discriminative classification with sets of image features” K. Grauman and T. Darrell
2017 “Actions as space-time shapes” M. Blank, L. Gorelick, E. Shechtman, M. Irani, and R. Basri
2015 “A Database of Human Segmented Natural Images and Its Application to Evaluating Segmentation Algorithms and Measuring Ecological Statistics” D. Martin, C. Fowlkes, D. Tal, J. Malik
2015 “Matching Shapes” S. Belongie, J. Malik, J. Puzicha
2013 “Snakes: Active Contour Models” M. Kass, A. Witkin, D. Terzopoulos
2013 “Indexing via color histograms” M. J. Swain, D. H. Ballard
2013 “Steerable filters for early vision, image analysis, and wavelet decomposition” B. Freeman, T. Adelson
2013 “A framework for the robust estimation of optical flow” M. Black and P. Anandan
2013 “Alignment by Maximization of Mutual Information” P. Viola, W. M. Wells III
2013 “In Defence of the 8-Point Algorithm” R. Hartley
2013 “Bilateral Filtering for Gray and Color Images” C. Tomasi, R. Manduchi
2013 “A Metric for Distributions with Applications to Image Databases” Y. Rubner, C. Tomasi, L. J. Guibas
2013 “Region Competition: Unifying Snakes, Region Growing, Energy/Bayes/MDL for Multi-band Image Segmentation” S. C. Zhu, T. S. Lee, A. Yuille
2013 “Flexible Camera Calibration by Viewing a Plane from Unknown Orientations” Z. Zhang
2013 “Texture Synthesis by Non-parametric Sampling” A. Efros, T. K. Leung
2011 “Object Recognition from Local Scale-Invariant Features” D. Lowe
2011 “Fast Approximate Energy Minimization via Graph Cuts” Y. Boykov, O. Veksler, R. Zabih
2011 “Geodesic Active Contours” V. Caselles, R. Kimmel, G. Sapiro
2009 “Geometric Hashing: A General and Efficient Model-Based Recognition Scheme” Y. Lamdan, H. J. Wolfson