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 |