Video compression with rate-distortion autoencoders A Habibian, T Rozendaal, JM Tomczak, TS Cohen Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 223 | 2019 |
Videostory: A new multimedia embedding for few-example recognition and translation of events A Habibian, T Mensink, CGM Snoek Proceedings of the 22nd ACM international conference on Multimedia, 17-26, 2014 | 117 | 2014 |
Computer Vision--ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part I D Fleet, T Pajdla, B Schiele, T Tuytelaars Springer, 2014 | 110* | 2014 |
Composite concept discovery for zero-shot video event detection A Habibian, T Mensink, CGM Snoek Proceedings of International Conference on Multimedia Retrieval, 17-24, 2014 | 91 | 2014 |
Video2vec embeddings recognize events when examples are scarce A Habibian, T Mensink, CGM Snoek IEEE transactions on pattern analysis and machine intelligence 39 (10), 2089 …, 2016 | 85 | 2016 |
Frameexit: Conditional early exiting for efficient video recognition A Ghodrati, BE Bejnordi, A Habibian Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 79 | 2021 |
Recommendations for video event recognition using concept vocabularies A Habibian, KEA van de Sande, CGM Snoek Proceedings of the 3rd ACM conference on International conference on …, 2013 | 74 | 2013 |
Skip-convolutions for efficient video processing A Habibian, D Abati, TS Cohen, BE Bejnordi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 51 | 2021 |
Evaluating multimedia features and fusion for example-based event detection GK Myers, CGM Snoek, R Nevatia, R Nallapati, J van Hout, S Pancoast, ... Fusion in Computer Vision: Understanding Complex Visual Content, 109-133, 2014 | 45 | 2014 |
MediaMill at TRECVID 2014: Searching Concepts, Objects, Instances and Events in Video. CGM Snoek, KEA van de Sande, D Fontijne, AH Habibian, M Jain, ... TRECVID 1 (2), 3, 2013 | 44 | 2013 |
Querying for video events by semantic signatures from few examples M Mazloom, A Habibian, CGM Snoek Proceedings of the 21st ACM international conference on Multimedia, 609-612, 2013 | 40 | 2013 |
Recommendations for recognizing video events by concept vocabularies A Habibian, CGM Snoek Computer Vision and Image Understanding 124, 110-122, 2014 | 30 | 2014 |
Predicting subject body poses and subject movement intent using probabilistic generative models MSALI AKBARIAN, A HABIBIAN, KEA VAN DE SANDE US Patent 10,937,173, 2021 | 29 | 2021 |
Discovering semantic vocabularies for cross-media retrieval A Habibian, T Mensink, CGM Snoek Proceedings of the 5th ACM on International Conference on Multimedia …, 2015 | 25 | 2015 |
Encoding concept prototypes for video event detection and summarization M Mazloom, A Habibian, D Liu, CGM Snoek, SF Chang Proceedings of the 5th ACM on International Conference on Multimedia …, 2015 | 19 | 2015 |
A selective weighted late fusion for visual concept recognition N Liu, E Dellandrea, B Tellez, L Chen Fusion in Computer Vision: Understanding Complex Visual Content, 1-28, 2014 | 18 | 2014 |
Video compression using deep generative models A Habibian, TJ Van Rozendaal, TS Cohen US Patent 11,729,406, 2023 | 17 | 2023 |
Semantic multisensory embeddings for video search by text A Habibian, TEJ Mensink, CGM Snoek US Patent App. 15/080,501, 2017 | 17 | 2017 |
Failure detection for a neural network object tracker A Habibian, CGM Snoek US Patent 10,740,654, 2020 | 16 | 2020 |
Salisa: Saliency-based input sampling for efficient video object detection B Ehteshami Bejnordi, A Habibian, F Porikli, A Ghodrati European Conference on Computer Vision, 300-316, 2022 | 15 | 2022 |