Anna Kukleva
I’m Anna Kukleva, a postdoctoral researcher at MPII. I received my a PhD at Computer Vision and Machine Learning department at Max Plank Institute for Informatics, where I was supervised by Bernt Schiele. During my PhD, my research involved close collaborations with Hilde Kuehne (Tuebingen AI Center), and Christian Rupprecht (Oxford). I’ve visited Meta FAIR and FRL labs as research intern. Particularly, in Nimble XR Input team at FRL, we were working on egocentric videos with Fadime Sener. Prior to my PhD, I had the opportunity to work in WILLOW team at Inria Paris on multi-modal understanding of social human behaviour with Makarand Tapaswi and Ivan Laptev. During my master, I’ve been working on unsupervised video segmentation in Uni Bonn in the lab of Jürgen Gall.
My research focuses on image and multi-modal video recognition, with a specific interest in learning representations through self-supervised, semi-supervised, and rarely fully-supervised methods. My focus extends to exploring the transferability of these methods to few-shot and open-set generalization scenarios.
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08/24:     Defended my PhD! 🎉 👩🎓
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07/24:     Gave a talk on learning with less supervision at SprintML, CISPA
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07/24:     1 paper accepted at ECCV 2024!
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06/24:     I'll serve as Area Chair for WACV 2025
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06/24:     Top reviewer at CVPR 2024
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03/24:     Got accepted to Doctoral Consortium at CVPR24
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03/24:     Gave a talk on learning with less supervision at VGG Reading Group, Oxford
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03/24:     Gave a talk on learning with less supervision at University of Siegen
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02/24:     2 papers accepted at CVPR 2024!
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12/23:     Our workshop "LPVL" is accepted to CVPR24! Stay tuned!
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11/23:     Top reviewer at NeurIPS 2023
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08/23:     Served as Area Chair for WACV 2024
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07/23:     3 papers accepted at ICCV 2023!
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05/23:     Joined Meta FRL as a research intern. Working with Fadime Sener
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02/23:     Top reviewer at AISTAT 2023
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01/23:     1 paper accepted at ICLR 2023
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HowToCaption: Prompting LLMs to Transform Video Annotations at Scale
Nina Shvetsova*, Anna Kukleva*, Xudong Hong, Christian Rupprecht, Bernt Schiele, Hilde Kuehne
(*equal contribution)
ECCV, 2024
Paper | Code
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X-MIC: Cross-Modal Instance Conditioning for Egocentric Action Generalization
Anna Kukleva, Fadime Sener, Edoardo Remelli, Bugra Tekin, Eric Sauser , Bernt Schiele, Shugao Ma
CVPR, 2024
Paper | Code
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OrCo: Towards Better Generalization via Orthogonality and Contrast for Few-Shot Class-Incremental Learning
Noor Ahmed*, Anna Kukleva*, Bernt Schiele
(*equal contribution)
CVPR, 2024 (Highlight)
Paper | Code
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In-Style: Bridging Text and Uncurated Videos with Style Transfer for Text-Video Retrieval
Nina Shvetsova*, Anna Kukleva*, Bernt Schiele, Hilde Kuehne
(*equal contribution)
ICCV, 2023
Paper | Code
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SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning
Yue Fan, Anna Kukleva, Dengxin Dai, Bernt Schiele
ICCV, 2023
Paper | Code
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Learning by Sorting: Self-supervised Learning with Group Ordering Constraints
Nina Shvetsova, Felix Petersen, Anna Kukleva, Bernt Schiele, Hilde Kuehne
ICCV, 2023
Paper
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Revisiting Consistency Regularization for Semi-Supervised Learning
Yue Fan, Anna Kukleva, Bernt Schiele
IJCV, 2023
Paper
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Temperature Schedules for self-supervised contrastive methods on long-tail data
Anna Kukleva*, Moritz Boehle*, Bernt Schiele, Hilde Kuehne, Christian Rupprecht
(*equal contribution)
ICLR, 2023
Paper | Code
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Leveraging Self-Supervised Training for Unintentional Action Recognition
Enea Duka*, Anna Kukleva*, Bernt Schiele
(*equal contribution)
ECCVW, 2022
Paper | Code
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CycDA: Unsupervised Cycle Domain Adaptation from Image to Video
Wei Lin, Anna Kukleva, Kunyang Sun, Horst Possegger, Hilde Kuehne, Horst Bischof
ECCV, 2022
Paper
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TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering
Wei Lin, Anna Kukleva, Horst Possegger, Hilde Kuehne, Horst Bischof
CEUR Workshop, 2023
Paper
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CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning
Yue Fan, Dengxin Dai, Anna Kukleva, Bernt Schiele
CVPR, 2022
Paper | Code
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Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration Without Forgetting
Anna Kukleva, Hilde Kuehne, Bernt Schiele
ICCV, 2021
Paper | Code
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Joint Visual-Temporal Embedding for Unsupervised Learning of Actions in Untrimmed Sequences
Rosaura G. VidalMata, Walter J. Scheirer, Anna Kukleva, David Cox, Hilde Kuehne
WACV, 2021
Paper
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Learning Interactions and Relationships between Movie Characters
Anna Kukleva, Makarand Tapaswi, Ivan Laptev
CVPR, 2020 (Oral)
Paper | Code
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Utilizing Temporal Information in Deep Convolutional Network for Efficient Soccer Ball Detection and Tracking
Anna Kukleva*, Mohammad Asif Khan*, Hafez Farazi, Sven Behnke
(*equal contribution)
RoboCup, 2019 (Oral)
Paper | Code
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Unsupervised Learning of Action Classes with Continuous Temporal Embedding
Anna Kukleva*, Hilde Kuehne*, Fadime Sener, Jürgen Gall
(*equal contribution)
CVPR, 2019
Paper | Code
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Talks
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07/2024: Talk on learning with less supervision at SprintML, CISPA
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03/2024: Talk on learning with less supervision at VGG Reading Group, Oxford
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03/2024: Talk on learning with less supervision at University of Siegen
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02/2024: Moderate Q&A session of amazing talk by Yuxiong Wang who talks about "Bridging Generative & Discriminative Learning in the Open Worlds", Virtual
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01/2022: Talk at Compuer Vision Talks, Virtual
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12/2020: Talk at 6th Christmas Colloquium on Computer Vision 2020, Samsung AI Center Moscow, Virtual
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08/2020: Talk at DLCV Practioner’s Evening, Virtual
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01/2020: Talk at Abhinav Gupta’s group at CMU in Pittsburgh, USA
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11/2019: Talk at WILLOW-ENPC-Berkeley Workshop on Vision and Robotics in Paris, France
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09/2019: Poster at BMVA symposium on Video Understanding in London, UK
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06/2019: Poster at WiCV workshop in conjunction with CVPR 2019 in Long Beach, USA
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Academic
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Area Chair: WACV24, WACV25
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Top Reviewer: AISTAT23, NeurIPS23, CVPR24
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Reviewer: CVPR21-24, ICCV21-23, ECCV22-24, AISTAT23, NeurIPS23-24, WACV21-22, PAMI, IJCV, TMM, ACMMM21
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07/2021: Grace-Hopper-Award (Master Thesis Award), Uni Bonn
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ECCV 2020: Coorganizing the WiCV workshop, Virtual
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CVPR 2024: Coorganizing workshop "Learning from Procedural Videos and Language: What is Next?", Seattle
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