210 citations · 802 across the 39 of their papers we have counts for
15 papers · 1 filter
SSB: Simple but Strong Baseline for Boosting Performance of Open-Set Semi-Supervised Learning
Yue Fan, Anna Kukleva, Dengxin Dai +1
Semi-supervised learning (SSL) methods effectively leverage unlabeled data to improve model generalization. However, SSL models often underperform in open-set scenarios, where unla…
Wakening Past Concepts without Past Data: Class-Incremental Learning from Online Placebos
Yaoyao Liu, Yingying Li, Bernt Schiele +1
Not forgetting old class knowledge is a key challenge for class-incremental learning (CIL) when the model continuously adapts to new classes. A common technique to address this is…
In-Style: Bridging Text and Uncurated Videos with Style Transfer for Text-Video Retrieval
Nina Shvetsova, Anna Kukleva, Bernt Schiele +1
Large-scale noisy web image-text datasets have been proven to be efficient for learning robust vision-language models. However, when transferring them to the task of video retrieva…
Certified Robust Models with Slack Control and Large Lipschitz Constants
Max Losch, David Stutz, Bernt Schiele +1
Despite recent success, state-of-the-art learning-based models remain highly vulnerable to input changes such as adversarial examples. In order to obtain certifiable robustness aga…
Object-Centric Multiple Object Tracking
Zixu Zhao, Jiaze Wang, Max Horn +13
Unsupervised object-centric learning methods allow the partitioning of scenes into entities without additional localization information and are excellent candidates for reducing th…
UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation
Haiyang Wang, Hao Tang, Shaoshuai Shi +4
Jointly processing information from multiple sensors is crucial to achieving accurate and robust perception for reliable autonomous driving systems. However, current 3D perception…