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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News

08/24:     Defended my PhD! 🎉 👩‍🎓

07/24:     Gave a talk on learning with less supervision at SprintML, CISPA

07/24:     1 paper accepted at ECCV 2024!

06/24:     I'll serve as Area Chair for WACV 2025

06/24:     Top reviewer at CVPR 2024

03/24:     Got accepted to Doctoral Consortium at CVPR24

03/24:     Gave a talk on learning with less supervision at VGG Reading Group, Oxford

03/24:     Gave a talk on learning with less supervision at University of Siegen

02/24:     2 papers accepted at CVPR 2024!

12/23:     Our workshop "LPVL" is accepted to CVPR24! Stay tuned!

11/23:     Top reviewer at NeurIPS 2023

08/23:     Served as Area Chair for WACV 2024

07/23:     3 papers accepted at ICCV 2023!

05/23:     Joined Meta FRL as a research intern. Working with Fadime Sener

02/23:     Top reviewer at AISTAT 2023

01/23:     1 paper accepted at ICLR 2023
Publications
HowToCaption

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

XMIC

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

OrCo

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

InStyle

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

SBB

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

Sorting

Learning by Sorting: Self-supervised Learning with Group Ordering Constraints
Nina Shvetsova, Felix Petersen, Anna Kukleva, Bernt Schiele, Hilde Kuehne
ICCV, 2023

Paper

Rev

Revisiting Consistency Regularization for Semi-Supervised Learning
Yue Fan, Anna Kukleva, Bernt Schiele
IJCV, 2023

Paper

Temperature

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

Oops

Leveraging Self-Supervised Training for Unintentional Action Recognition
Enea Duka*, Anna Kukleva*, Bernt Schiele
(*equal contribution)
ECCVW, 2022

Paper | Code

CycDA

CycDA: Unsupervised Cycle Domain Adaptation from Image to Video
Wei Lin, Anna Kukleva, Kunyang Sun, Horst Possegger, Hilde Kuehne, Horst Bischof
ECCV, 2022

Paper

taec

TAEC: Unsupervised Action Segmentation with Temporal-Aware Embedding and Clustering
Wei Lin, Anna Kukleva, Horst Possegger, Hilde Kuehne, Horst Bischof
CEUR Workshop, 2023

Paper

CoSSL

CoSSL: Co-Learning of Representation and Classifier for Imbalanced Semi-Supervised Learning
Yue Fan, Dengxin Dai, Anna Kukleva, Bernt Schiele
CVPR, 2022

Paper | Code

FSL

Generalized and Incremental Few-Shot Learning by Explicit Learning and Calibration Without Forgetting
Anna Kukleva, Hilde Kuehne, Bernt Schiele
ICCV, 2021

Paper | Code

wacv21

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

movies

Learning Interactions and Relationships between Movie Characters
Anna Kukleva, Makarand Tapaswi, Ivan Laptev
CVPR, 2020 (Oral)

Paper | Code

robo

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

cet

Unsupervised Learning of Action Classes with Continuous Temporal Embedding
Anna Kukleva*, Hilde Kuehne*, Fadime Sener, Jürgen Gall
(*equal contribution)
CVPR, 2019

Paper | Code


Talks


Academic



Stolen from Jon Barron. Big thanks!