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Anna Kukleva
I’m a Research Scientist at Meta. Previously, I was a postdoc at MPII, where I was involved in the VIA Center, a collaborative initiative with Google. I received my a PhD at Max Plank Institute for Informatics under supervision of Bernt Schiele and was honored with the Otto-Hahn-Medal for an outstanding PhD thesis. 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. Prior to my PhD, I had the opportunity to work in WILLOW team at Inria Paris with Makarand Tapaswi and Ivan Laptev. During my master, I’ve been working 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.
Email /
CV /
Google Scholar /
Github /
LinkedIn
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| 2026 |
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Do Instance Priors Help Weakly Supervised Semantic Segmentation?
Anurag Das, Anna Kukleva, Xinting Hu, Yuki M. Asano, Bernt Schiele
TMLR, 2026
Paper
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TTA-Vid: Generalized Test-Time Adaptation for Video Reasoning
Soumya Shamarao Jahagirdar, Edson Araujo, Anna Kukleva, M. Jehanzeb Mirza, Saurabhchand Bhati, Samuel Thomas, Brian Kingsbury, Rogerio Feris, James R. Glass, Hilde Kuehne
preprint, arxiv 2026
Paper
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MM-TS: Multi-Modal Temperature and Margin Schedules for Contrastive Learning with Long-Tail Data
Siarhei Sheludzko, Dhimitrios Duka, Bernt Schiele, Hilde Kuehne, Anna Kukleva
WACV, 2026 (Oral)
Paper
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When LLaVA Meets Objects: Token Composition for Vision-Language-Models
Soumya Jahagirdar, Walid Bousselham, Anna Kukleva, Hilde Kuehne
preprint, arxiv 2026
Paper
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RefAM: Attention Magnets for Zero-Shot Referral Segmentation
Anna Kukleva*, Enis Simsar*, Alessio Tonioni, Muhammad Ferjad Naeem, Federico Tombari, Jan Eric Lenssen, Bernt Schiele
(*equal contribution)
TMLR, 2026
Paper | Code | Project
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Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs
Selim Kuzucu, Muhammad Ferjad Naeem, Anna Kukleva, Federico Tombari, Bernt Schiele
TMLR, 2026
Paper
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| 2025 |
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T-FAKE: Synthesizing Thermal Images for Facial Landmarking
Philipp Flotho*, Moritz Piening*, Anna Kukleva, Gabriele Steidl
(*equal contribution)
CVPR, 2025
Paper | Dataset
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VideoGEM: Training-free Action Grounding in Videos
Felix Vogel, Walid Bousselham, Anna Kukleva, Nina Shvetsova, Hilde Kuehne
CVPR, 2025
Paper | Code
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| 2024 |
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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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| 2023 |
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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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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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| 2022 |
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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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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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| 2021 |
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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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| 2020 |
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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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| 2019 |
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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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09/2026: Keynote at the WiCV workshop at ECCV 2026, Malmö, Sweden
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09/2026: Invited talk at the LIMIT workshop "Representation Learning with Very Limited Resources" at ECCV 2026, Malmö, Sweden
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11/2025: Talk about our RefAM paper at ResearchTrend.AI
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10/2025: Visited Visual Recognition Group (VRG) and talked about "Unconventional LLM usage in vision tasks" at the 50th Pattern Recognition and Computer Vision Colloquium , Czech Technical University, Prague
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02/2025: Talk on advancing video recognition with less supervision at FunAI group, UTN
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09/2024: Research Spotlight Talk at GCPR 2024
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08/2024: "HowToCaption: Prompting LLMs to Transform Video Annotations at Scale" at The 57th session of MultimodalWeekly Twelve Labs
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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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Reviewing
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Area Chair: WACV24-26, NeurIPS25-26, ICML26, ICLR27
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Reviewer: CVPR21-26 (w/o 25), ICCV21-23, ECCV22-24, AISTAT23, NeurIPS23-24, ICML25, WACV21-22, PAMI, IJCV, TMM, ACMMM21, Nature CommsEng
Awards
Organizing
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