Efficient Discriminative Projections for Compact Binary Descriptors. - Tomasz Trzcinski; Vincent Lepetit (ECCV (1), 2012)

Learning Image Descriptors with the Boosting-Trick. - Tomasz Trzcinski; C. Mario Christoudias; Vincent Lepetit; Pascal Fua (NIPS, 2012)

BRIEF: Computing a Local Binary Descriptor Very Fast. - Michael Calonder; Vincent Lepetit; Mustafa Özuysal; Tomasz Trzcinski; Christoph Strecha; Pascal Fua (IEEE Trans. Pattern Anal. Mach. Intell., 2012)

Thick boundaries in binary space and their influence on nearest-neighbor search. - Tomasz Trzcinski; Vincent Lepetit; Pascal Fua (Pattern Recognit. Lett., 2012)

Boosting Binary Keypoint Descriptors. - Tomasz Trzcinski; C. Mario Christoudias; Pascal Fua; Vincent Lepetit (CVPR, 2013)

Receptive Fields Selection for Binary Feature Description. - Bin Fan 001; Qingqun Kong; Tomasz Trzcinski; Zhiheng Wang 001; Chunhong Pan; Pascal Fua (IEEE Trans. Image Process., 2014)

Learning and Matching Binary Local Feature Descriptors. - Tomasz Trzcinski (2014)

Learning Image Descriptors with Boosting. - Tomasz Trzcinski; C. Mario Christoudias; Vincent Lepetit (IEEE Trans. Pattern Anal. Mach. Intell., 2015)

Deep Alignment Network: A Convolutional Neural Network for Robust Face Alignment. - Marek Kowalski; Jacek Naruniec; Tomasz Trzcinski (CVPR Workshops, 2017)

What Looks Good with my Sofa: Ensemble Multimodal Search for Interior Design. - Ivona Tautkute; Aleksandra Mozejko; Wojciech Stokowiec; Tomasz Trzcinski; Lukasz Brocki; Krzysztof Marasek (FedCSIS, 2017)

Evaluation of Hashing Methods Performance on Binary Feature Descriptors. - Jacek Komorowski; Tomasz Trzcinski (IP&C, 2017)

Speaker Diarization Using Deep Recurrent Convolutional Neural Networks for Speaker Embeddings. - Pawel Cyrta; Tomasz Trzcinski; Wojciech Stokowiec (ISAT (1), 2017)

Shallow Reading with Deep Learning: Predicting Popularity of Online Content Using only Its Title. - Wojciech Stokowiec; Tomasz Trzcinski; Krzysztof Wolk; Krzysztof Marasek; Przemyslaw Rokita (ISMIS, 2017)

Recurrent Neural Networks for Online Video Popularity Prediction. - Tomasz Trzcinski; Pawel Andruszkiewicz; Tomasz Bochenski; Przemyslaw Rokita (ISMIS, 2017)

Random Binary Search Trees for Approximate Nearest Neighbour Search in Binary Space. - Michal Komorowski; Tomasz Trzcinski (PReMI, 2017)

Understanding aesthetics in photography using deep convolutional neural networks. - Maciej Suchecki; Tomasz Trzcinski (SPA, 2017)

What Looks Good with my Sofa: Multimodal Search Engine for Interior Design. - Ivona Tautkute; Aleksandra Mozejko; Wojciech Stokowiec; Tomasz Trzcinski; Lukasz Brocki; Krzysztof Marasek (CoRR, 2017)

Random Binary Trees for Approximate Nearest Neighbour Search in Binary Space. - Michal Komorowski; Tomasz Trzcinski (CoRR, 2017)

Predicting Popularity of Online Videos Using Support Vector Regression. - Tomasz Trzcinski; Przemyslaw Rokita (IEEE Trans. Multim., 2017)

Siamese Generative Adversarial Privatizer for Biometric Data. - Witold Oleszkiewicz; Peter Kairouz; Karol J. Piczak; Ram Rajagopal; Tomasz Trzcinski (ACCV (5), 2018)

Recognizing Emotions with EmotionalDAN. - Ivona Tautkute; Tomasz Trzcinski; Adam Bielski (CompIMAGE, 2018)

Pay Attention to Virality: Understanding Popularity of Social Media Videos With the Attention Mechanism. - Adam Bielski; Tomasz Trzcinski (CVPR Workshops, 2018)

I Know How You Feel: Emotion Recognition With Facial Landmarks. - Ivona Tautkute; Tomasz Trzcinski; Adam Bielski (CVPR Workshops, 2018)

Interest Point Detectors Stability Evaluation on ApolloScape Dataset. - Jacek Komorowski; Konrad Czarnota; Tomasz Trzcinski; Lukasz Dabala; Simon Lynen (ECCV Workshops (5), 2018)

SConE: Siamese Constellation Embedding Descriptor for Image Matching. - Tomasz Trzcinski; Jacek Komorowski; Lukasz Dabala; Konrad Czarnota; Grzegorz Kurzejamski; Simon Lynen (ECCV Workshops (1), 2018)

Aggregation of Binary Feature Descriptors for Compact Scene Model Representation in Large Scale Structure-from-Motion Applications. - Jacek Komorowski; Tomasz Trzcinski (ICCVG, 2018)

Extracting Textual Overlays from Social Media Videos Using Neural Networks. - Adam Slucki; Tomasz Trzcinski; Adam Bielski; Pawel Cyrta (ICCVG, 2018)

Estimating Achilles Tendon Healing Progress with Convolutional Neural Networks. - Norbert Kapinski; Jakub Zielinski; Bartosz A. Borucki; Tomasz Trzcinski; Beata Ciszkowska-Lyson; Krzysztof S. Nowinski (MICCAI (2), 2018)

BinGAN: Learning Compact Binary Descriptors with a Regularized GAN. - Maciej Zieba; Piotr Semberecki; Tarek El-Gaaly; Tomasz Trzcinski (NeurIPS, 2018)

Understanding Multimodal Popularity Prediction of Social Media Videos With Self-Attention. - Adam Bielski; Tomasz Trzcinski (IEEE Access, 2018)

SocialML: machine learning for social media video creators. - Tomasz Trzcinski; Adam Bielski; Pawel Cyrta; Matthew Zak (CoRR, 2018)

Siamese Generative Adversarial Privatizer for Biometric Data. - Witold Oleszkiewicz; Tomasz Wlodarczyk; Karol J. Piczak; Tomasz Trzcinski; Peter Kairouz; Ram Rajagopal (CoRR, 2018)

Neural Comic Style Transfer: Case Study. - Maciej Pesko; Tomasz Trzcinski (CoRR, 2018)

Adversarial Autoencoders for Generating 3D Point Clouds. - Maciej Zamorski; Maciej Zieba; Rafal Nowak; Wojciech Stokowiec; Tomasz Trzcinski (CoRR, 2018)

Estimation of Preterm Birth Markers with U-Net Segmentation Network. - Tomasz Wlodarczyk; Szymon Plotka; Tomasz Trzcinski; Przemyslaw Rokita; Nicole Sochacki-Wójcicka; Michal Lipa; Jakub Wójcicki (SUSI/PIPPI@MICCAI, 2019)

Monitoring Achilles Tendon Healing Progress in Ultrasound Imaging with Convolutional Neural Networks. - Piotr Woznicki; Przemyslaw Przybyszewski; Norbert Kapinski; Jakub Zielinski; Beata Ciszkowska-Lyson; Bartosz A. Borucki; Tomasz Trzcinski; Krzysztof Nowinski (SUSI/PIPPI@MICCAI, 2019)

DeepStyle: Multimodal Search Engine for Fashion and Interior Design. - Ivona Tautkute; Tomasz Trzcinski; Aleksander Skorupa; Lukasz Brocki; Krzysztof Marasek (IEEE Access, 2019)

Random Binary Search Trees for approximate nearest neighbour search in binary spaces. - Michal Komorowski; Tomasz Trzcinski (Appl. Soft Comput., 2019)

Plugin Networks for Inference under Partial Evidence. - Michal Koperski; Tomasz K. Konopczynski; Piotr Semberecki; Tomasz Trzcinski (CoRR, 2019)

Late fusion of deep learning and hand-crafted features for Achilles tendon healing monitoring. - Norbert Kapinski; Jedrzej M. Nowosielski; Maciej E. Marchwiany; Jakub Zielinski; Beata Ciszkowska-Lyson; Bartosz A. Borucki; Tomasz Trzcinski; Krzysztof S. Nowinski (CoRR, 2019)

Comixify: Transform Video Into Comics. - Maciej Pesko; Adam Svystun; Pawel Andruszkiewicz; Przemyslaw Rokita; Tomasz Trzcinski (Fundam. Informaticae, 2019)

Classifying and Visualizing Emotions with Emotional DAN. - Ivona Tautkute; Tomasz Trzcinski (Fundam. Informaticae, 2019)

Synthetic Image Translation for Football Players Pose Estimation. - Michal Sypetkowski; Grzegorz Sarwas; Tomasz Trzcinski (J. Univers. Comput. Sci., 2019)

SuperNCN: Neighbourhood Consensus Network for Robust Outdoor Scenes Matching. - Grzegorz Kurzejamski; Jacek Komorowski; Lukasz Dabala; Konrad Czarnota; Simon Lynen; Tomasz Trzcinski (ACIVS, 2020)

Hypernetwork approach to generating point clouds. - Przemyslaw Spurek; Sebastian Winczowski; Jacek Tabor; Maciej Zamorski; Maciej Zieba; Tomasz Trzcinski (ICML, 2020)

Comixify: turning videos into comics. - Tomasz Trzcinski (AI4Narratives@IJCAI, 2020)

Spontaneous Preterm Birth Prediction Using Convolutional Neural Networks. - Tomasz Wlodarczyk; Szymon Plotka; Przemyslaw Rokita; Nicole Sochacki-Wójcicka; Jakub Wójcicki; Michal Lipa; Tomasz Trzcinski (ASMUS/PIPPI@MICCAI, 2020)

Multimodal Dance Recognition. - Monika Wysoczanska; Tomasz Trzcinski (VISIGRAPP (5: VISAPP), 2020)

Plugin Networks for Inference under Partial Evidence. - Michal Koperski; Tomasz K. Konopczynski; Rafal Nowak; Piotr Semberecki; Tomasz Trzcinski (WACV, 2020)

Understanding the robustness of deep neural network classifiers for breast cancer screening. - Witold Oleszkiewicz; Taro Makino; Stanislaw Jastrzebski; Tomasz Trzcinski; Linda Moy; Kyunghyun Cho; Laura Heacock; Krzysztof J. Geras (CoRR, 2020)

End-to-end Sinkhorn Autoencoder with Noise Generator. - Kamil Deja; Jan Dubinski; Piotr Nowak; Sandro Wenzel; Tomasz Trzcinski (CoRR, 2020)

HyperFlow: Representing 3D Objects as Surfaces. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (CoRR, 2020)

Adversarial autoencoders for compact representations of 3D point clouds. - Maciej Zamorski; Maciej Zieba; Piotr Klukowski; Rafal Nowak; Karol Kurach; Wojciech Stokowiec; Tomasz Trzcinski (Comput. Vis. Image Underst., 2020)

Large-Scale Topological Radar Localization Using Learned Descriptors. - Jacek Komorowski; Monika Wysoczanska; Tomasz Trzcinski (ICONIP (2), 2021)

On Robustness of Generative Representations Against Catastrophic Forgetting. - Wojciech Masarczyk; Kamil Deja; Tomasz Trzcinski (ICONIP (6), 2021)

FetalNet: Multi-task Deep Learning Framework for Fetal Ultrasound Biometric Measurements. - Szymon Plotka; Tomasz Wlodarczyk; Adam Klasa; Michal Lipa; Arkadiusz Sitek; Tomasz Trzcinski (ICONIP (6), 2021)

Continual Learning of 3D Point Cloud Generators. - Michal Sadowski; Karol J. Piczak; Przemyslaw Spurek; Tomasz Trzcinski (ICONIP (1), 2021)

SynthTriplet GAN: Synthetic Query Expansion for Multimodal Retrieval. - Ivona Tautkute; Tomasz Trzcinski (ICONIP (4), 2021)

Explaining Self-Supervised Image Representations with Visual Probing. - Dominika Basaj; Witold Oleszkiewicz; Igor Sieradzki; Michal Górszczak; Barbara Rychalska; Tomasz Trzcinski; Bartosz Zielinski 001 (IJCAI, 2021)

BinPlay: A Binary Latent Autoencoder for Generative Replay Continual Learning. - Kamil Deja; Pawel Wawrzynski; Daniel Marczak; Wojciech Masarczyk; Tomasz Trzcinski (IJCNN, 2021)

MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition. - Jacek Komorowski; Monika Wysoczanska; Tomasz Trzcinski (IJCNN, 2021)

Non-Gaussian Gaussian Processes for Few-Shot Regression. - Marcin Sendera; Jacek Tabor; Aleksandra Nowak 001; Andrzej Bedychaj; Massimiliano Patacchiola; Tomasz Trzcinski; Przemyslaw Spurek; Maciej Zieba (NeurIPS, 2021)

Zero Time Waste: Recycling Predictions in Early Exit Neural Networks. - Maciej Wolczyk; Bartosz Wójcik; Klaudia Balazy; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (NeurIPS, 2021)

Global Point Cloud Descriptor for Place Recognition in Indoor Environments. - Jacek Komorowski; Grzegorz Kurzejamski; Monika Wysoczanska; Tomasz Trzcinski (VISIGRAPP (5: VISAPP), 2021)

End-to-End Sinkhorn Autoencoder With Noise Generator. - Kamil Deja; Jan Dubinski; Piotr Nowak; Sandro Wenzel; Przemyslaw Spurek; Tomasz Trzcinski (IEEE Access, 2021)

Modeling 3D Surface Manifolds with a Locally Conditioned Atlas. - Przemyslaw Spurek; Sebastian Winczowski; Maciej Zieba; Tomasz Trzcinski; Kacper Kania (CoRR, 2021)

TrajeVAE - Controllable Human Motion Generation from Trajectories. - Kacper Kania; Marek Kowalski; Tomasz Trzcinski (CoRR, 2021)

Convolutional Neural Networks in Orthodontics: a review. - Szymon Plotka; Tomasz Wlodarczyk; Ryszard Szczerba; Przemyslaw Rokita; Patrycja Bartkowska; Oskar Komisarek; Artur Matthews-Brzozowski; Tomasz Trzcinski (CoRR, 2021)

Multiband VAE: Latent Space Partitioning for Knowledge Consolidation in Continual Learning. - Kamil Deja; Pawel Wawrzynski; Daniel Marczak; Wojciech Masarczyk; Tomasz Trzcinski (CoRR, 2021)

HyperColor: A HyperNetwork Approach for Synthesizing Auto-colored 3D Models for Game Scenes Population. - Ivan Kostiuk; Przemyslaw Stachura; Slawomir Konrad Tadeja; Tomasz Trzcinski; Przemyslaw Spurek (CoRR, 2021)

HyperCube: Implicit Field Representations of Voxelized 3D Models. - Magdalena Proszewska; Marcin Mazur; Tomasz Trzcinski; Przemyslaw Spurek (CoRR, 2021)

Representing point clouds with generative conditional invertible flow networks. - Michal Stypulkowski; Kacper Kania; Maciej Zamorski; Maciej Zieba; Tomasz Trzcinski; Jan Chorowski (Pattern Recognit. Lett., 2021)

Deep Learning for Automatic Detection of Qualitative Features of Lecturing. - Anna Wróblewska; Jozef Jasek; Bogdan Jastrzebski; Stanislaw Pawlak; Anna Grzywacz; Siew Ann Cheong; Seng Chee Tan; Tomasz Trzcinski; Janusz A. Holyst (AIED (1), 2022)

CoNeRF: Controllable Neural Radiance Fields. - Kacper Kania; Kwang Moo Yi; Marek Kowalski; Tomasz Trzcinski; Andrea Tagliasacchi (CVPR, 2022)

Noninvasive Estimation of Mean Pulmonary Artery Pressure Using MRI, Computer Models, and Machine Learning. - Michal K. Grzeszczyk; Tadeusz Satlawa; Angela Lungu; Andrew J. Swift; Andrew J. Narracott; D. Rodney Hose; Tomasz Trzcinski; Arkadiusz Sitek (ICCS (3), 2022)

Which Visual Features Impact the Performance of Target Task in Self-supervised Learning? - Witold Oleszkiewicz; Dominika Basaj; Tomasz Trzcinski; Bartosz Zielinski 001 (ICCS (1), 2022)

Post-error Correction for Quantum Annealing Processor Using Reinforcement Learning. - Tomasz Smierzchalski; Lukasz Pawela; Zbigniew Puchala; Tomasz Trzcinski; Bartlomiej Gardas (ICCS (4), 2022)

POTHER: Patch-Voted Deep Learning-Based Chest X-ray Bias Analysis for COVID-19 Detection. - Tomasz Szczepanski; Arkadiusz Sitek; Tomasz Trzcinski; Szymon Plotka (ICCS (1), 2022)

Continual Learning with Guarantees via Weight Interval Constraints. - Maciej Wolczyk; Karol J. Piczak; Bartosz Wójcik; Lukasz Pustelnik; Pawel Morawiecki; Jacek Tabor; Tomasz Trzcinski; Przemyslaw Spurek (ICML, 2022)

Selectively Increasing the Diversity of GAN-Generated Samples. - Jan Dubinski; Kamil Deja; Sandro Wenzel; Przemyslaw Rokita; Tomasz Trzcinski (ICONIP (1), 2022)

Progressive Latent Replay for Efficient Generative Rehearsal. - Stanislaw Pawlak; Filip Szatkowski; Michal Bortkiewicz; Jan Dubinski; Tomasz Trzcinski (ICONIP (4), 2022)

Multiband VAE: Latent Space Alignment for Knowledge Consolidation in Continual Learning. - Kamil Deja; Pawel Wawrzynski; Wojciech Masarczyk; Daniel Marczak; Tomasz Trzcinski (IJCAI, 2022)

HyperPocket: Generative Point Cloud Completion. - Przemyslaw Spurek; Artur Kasymov; Marcin Mazur; Diana Janik; Slawomir Konrad Tadeja; Lukasz Struski; Jacek Tabor; Tomasz Trzcinski (IROS, 2022)

BabyNet: Residual Transformer Module for Birth Weight Prediction on Fetal Ultrasound Video. - Szymon Plotka; Michal K. Grzeszczyk; Robert Brawura-Biskupski-Samaha; Pawel Gutaj; Michal Lipa; Tomasz Trzcinski; Arkadiusz Sitek (MICCAI (4), 2022)

On Analyzing Generative and Denoising Capabilities of Diffusion-based Deep Generative Models. - Kamil Deja; Anna Kuzina; Tomasz Trzcinski; Jakub M. Tomczak (NeurIPS, 2022)

FlowHMM: Flow-based continuous hidden Markov models. - Pawel Lorek; Rafal Nowak; Tomasz Trzcinski; Maciej Zieba (NeurIPS, 2022)

Logarithmic Continual Learning. - Wojciech Masarczyk; Pawel Wawrzynski; Daniel Marczak; Kamil Deja; Tomasz Trzcinski (IEEE Access, 2022)

Deep Learning Fetal Ultrasound Video Model Match Human Observers in Biometric Measurements. - Szymon Plotka; Adam Klasa; Aneta Lisowska; Joanna Seliga-Siwecka; Michal Lipa; Tomasz Trzcinski; Arkadiusz Sitek (CoRR, 2022)

A Deep Learning Approach for Automatic Detection of Qualitative Features of Lecturing. - Anna Wróblewska; Jozef Jasek; Bogdan Jastrzebski; Stanislaw Pawlak; Anna Grzywacz; Siew Ann Cheong; Tan Seng Chee; Tomasz Trzcinski; Janusz A. Holyst (CoRR, 2022)

Points2NeRF: Generating Neural Radiance Fields from 3D point cloud. - Dominik Zimny; Tomasz Trzcinski; Przemyslaw Spurek (CoRR, 2022)

HyperSound: Generating Implicit Neural Representations of Audio Signals with Hypernetworks. - Filip Szatkowski; Karol J. Piczak; Przemyslaw Spurek; Jacek Tabor; Tomasz Trzcinski (CoRR, 2022)

Emergency action termination for immediate reaction in hierarchical reinforcement learning. - Michal Bortkiewicz; Jakub Lyskawa; Pawel Wawrzynski; Mateusz Ostaszewski; Artur Grudkowski; Tomasz Trzcinski (CoRR, 2022)

Towards Unsupervised Visual Reasoning: Do Off-The-Shelf Features Know How to Reason? - Monika Wysoczanska; Tom Monnier; Tomasz Trzcinski; David Picard (CoRR, 2022)

General Hypernetwork Framework for Creating 3D Point Clouds. - Przemyslaw Spurek; Maciej Zieba; Jacek Tabor; Tomasz Trzcinski (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale. - Jacek Komorowski; Monika Wysoczanska; Tomasz Trzcinski (IEEE Robotics Autom. Lett., 2022)

BlendFields: Few-Shot Example-Driven Facial Modeling. - Kacper Kania; Stephan J. Garbin; Andrea Tagliasacchi; Virginia Estellers; Kwang Moo Yi; Julien Valentin; Tomasz Trzcinski; Marek Kowalski (CVPR, 2023)

Looking through the past: better knowledge retention for generative replay in continual learning. - Valeriya Khan; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

AR-TTA: A Simple Method for Real-World Continual Test-Time Adaptation. - Damian Sójka; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning. - Filip Szatkowski; Mateusz Pyla; Marcin Przewiezlikowski; Sebastian Cygert; Bartlomiej Twardowski; Tomasz Trzcinski (ICCV (Workshops), 2023)

Active Visual Exploration Based on Attention-Map Entropy. - Adam Pardyl; Grzegorz Rypesc; Grzegorz Kurzejamski; Bartosz Zielinski 001; Tomasz Trzcinski (IJCAI, 2023)

TabAttention: Learning Attention Conditionally on Tabular Data. - Michal K. Grzeszczyk; Szymon Plotka; Beata Rebizant; Katarzyna Kosinska-Kaczynska; Michal Lipa; Robert Brawura-Biskupski-Samaha; Przemyslaw Korzeniowski; Tomasz Trzcinski; Arkadiusz Sitek (MICCAI (7), 2023)

Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders. - Jan Dubinski; Stanislaw Pawlak; Franziska Boenisch; Tomasz Trzcinski; Adam Dziedzic (NeurIPS, 2023)

The Tunnel Effect: Building Data Representations in Deep Neural Networks. - Wojciech Masarczyk; Mateusz Ostaszewski; Ehsan Imani; Razvan Pascanu; Piotr Milos; Tomasz Trzcinski (NeurIPS, 2023)

Learning Data Representations with Joint Diffusion Models. - Kamil Deja; Tomasz Trzcinski; Jakub M. Tomczak (ECML/PKDD (2), 2023)

Hypernetworks Build Implicit Neural Representations of Sounds. - Filip Szatkowski; Karol J. Piczak; Przemyslaw Spurek; Jacek Tabor; Tomasz Trzcinski (ECML/PKDD (4), 2023)

Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations. - Witold Oleszkiewicz; Dominika Basaj; Igor Sieradzki; Michal Górszczak; Barbara Rychalska; Koryna Lewandowska; Tomasz Trzcinski; Bartosz Zielinski 001 (IEEE Access, 2023)

Can gamification reduce the burden of self-reporting in mHealth applications? Feasibility study using machine learning from smartwatch data to estimate cognitive load. - Michal K. Grzeszczyk; Paulina Adamczyk; Sylwia Marek; Ryszard Precikowski; Maciej Kus; M. Patrycja Lelujko; Rosmary Blanco; Tomasz Trzcinski; Arkadiusz Sitek; Maciej Malawski; Aneta Lisowska (CoRR, 2023)

Exploring Continual Learning of Diffusion Models. - Michal Zajac 005; Kamil Deja; Anna Kuzina; Jakub M. Tomczak; Tomasz Trzcinski; Florian Shkurti; Piotr Milos (CoRR, 2023)

Machine Learning methods for simulating particle response in the Zero Degree Calorimeter at the ALICE experiment, CERN. - Jan Dubinski; Kamil Deja; Sandro Wenzel; Przemyslaw Rokita; Tomasz Trzcinski (CoRR, 2023)

Generalized Continual Category Discovery. - Daniel Marczak; Grzegorz Rypesc; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (CoRR, 2023)

Bayesian Flow Networks in Continual Learning. - Mateusz Pyla; Kamil Deja; Bartlomiej Twardowski; Tomasz Trzcinski (CoRR, 2023)

On consequences of finetuning on data with highly discriminative features. - Wojciech Masarczyk; Tomasz Trzcinski; Mateusz Ostaszewski (CoRR, 2023)

CLIP-DINOiser: Teaching CLIP a few DINO tricks. - Monika Wysoczanska; Oriane Siméoni; Michaël Ramamonjisoa; Andrei Bursuc; Tomasz Trzcinski; Patrick Pérez (CoRR, 2023)

Noninvasive Estimation of Mean Pulmonary Artery Pressure Using MRI, Computer Models, and Machine Learning. - Michal K. Grzeszczyk; Tadeusz Satlawa; Angela Lungu; Andrew J. Swift; Andrew J. Narracott; Rod Hose; Tomasz Trzcinski; Arkadiusz Sitek (CoRR, 2023)

Disentangled Continual Learning: Separating Memory Edits from Model Updates. - Sebastian Dziadzio; Çagatay Yildiz; Gido M. van de Ven; Tomasz Trzcinski; Tinne Tuytelaars; Matthias Bethge (CoRR, 2023)

Continual learning on 3D point clouds with random compressed rehearsal. - Maciej Zamorski; Michal Stypulkowski; Konrad Karanowski; Tomasz Trzcinski; Maciej Zieba (Comput. Vis. Image Underst., 2023)

Zero time waste in pre-trained early exit neural networks. - Bartosz Wójcik; Marcin Przewiezlikowski; Filip Szatkowski; Maciej Wolczyk; Klaudia Balazy; Bartlomiej Krzepkowski; Igor T. Podolak; Jacek Tabor; Marek Smieja; Tomasz Trzcinski (Neural Networks, 2023)

BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery. - Szymon Plotka; Michal K. Grzeszczyk; Robert Brawura-Biskupski-Samaha; Pawel Gutaj; Michal Lipa; Tomasz Trzcinski; Ivana Isgum; Clara I. Sánchez; Arkadiusz Sitek (Comput. Biol. Medicine, 2023)

HyperColor: A HyperNetwork Approach for Synthesizing Autocolored 3-D Models for Game Scenes Population. - Ivan Kostiuk; Przemyslaw Stachura; Slawomir Konrad Tadeja; Tomasz Trzcinski; Przemyslaw Spurek (IEEE Trans. Games, 2023)

HyperCube: Implicit Field Representations of Voxelized 3D Models (Student Abstract). - Magdalena Proszewska; Marcin Mazur; Tomasz Trzcinski; Przemyslaw Spurek (AAAI, 2024)

RegFlow: Probabilistic Flow-Based Regression for Future Prediction. - Maciej Zieba; Marcin Przewiezlikowski; Marek Smieja; Jacek Tabor; Tomasz Trzcinski; Przemyslaw Spurek (ACIIDS (Companion 2), 2024)

Infinite dSprites for Disentangled Continual Learning: Separating Memory Edits from Generalization. - Sebastian Dziadzio; Çagatay Yildiz; Gido M. van de Ven; Tomasz Trzcinski; Tinne Tuytelaars; Matthias Bethge (CoLLAs, 2024)

Zero-Waste Machine Learning. - Tomasz Trzcinski; Bartlomiej Twardowski; Bartosz Zielinski 001; Kamil Adamczewski; Bartosz Wójcik (ECAI, 2024)

Revisiting Supervision for Continual Representation Learning. - Daniel Marczak; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (ECCV (6), 2024)

MAGMAX: Leveraging Model Merging for Seamless Continual Learning. - Daniel Marczak; Bartlomiej Twardowski; Tomasz Trzcinski; Sebastian Cygert (ECCV (85), 2024)

AdaGlimpse: Active Visual Exploration with Arbitrary Glimpse Position and Scale. - Adam Pardyl; Michal Wronka; Maciej Wolczyk; Kamil Adamczewski; Tomasz Trzcinski; Bartosz Zielinski 001 (ECCV (21), 2024)

Category Adaptation Meets Projected Distillation in Generalized Continual Category Discovery. - Grzegorz Rypesc; Daniel Marczak; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (ECCV (11), 2024)

CLIP-DINOiser: Teaching CLIP a Few DINO Tricks for Open-Vocabulary Semantic Segmentation. - Monika Wysoczanska; Oriane Siméoni; Michaël Ramamonjisoa; Andrei Bursuc; Tomasz Trzcinski; Patrick Pérez (ECCV (61), 2024)

Subgoal Reachability in Goal Conditioned Hierarchical Reinforcement Learning. - Michal Bortkiewicz; Jakub Lyskawa; Pawel Wawrzynski; Mateusz Ostaszewski; Artur Grudkowski; Bartlomiej Sobieski; Tomasz Trzcinski (ICAART (1), 2024)

Modeling 3D Surfaces with a Locally Conditioned Atlas. - Przemyslaw Spurek; Sebastian Winczowski; Maciej Zieba; Tomasz Trzcinski; Kacper Kania; Marcin Mazur (ICCS (2), 2024)

Divide and not forget: Ensemble of selectively trained experts in Continual Learning. - Grzegorz Rypesc; Sebastian Cygert; Valeriya Khan; Tomasz Trzcinski; Bartosz Zielinski 001; Bartlomiej Twardowski (ICLR, 2024)

Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning. - Michal Nauman; Michal Bortkiewicz; Piotr Milos; Tomasz Trzcinski; Mateusz Ostaszewski; Marek Cygan (ICML, 2024)

TabMixer: Noninvasive Estimation of the Mean Pulmonary Artery Pressure via Imaging and Tabular Data Mixing. - Michal K. Grzeszczyk; Przemyslaw Korzeniowski; Samer Alabed; Andrew J. Swift; Tomasz Trzcinski; Arkadiusz Sitek (MICCAI (5), 2024)

Let Me DeCode You: Decoder Conditioning with Tabular Data. - Tomasz Szczepanski; Michal K. Grzeszczyk; Szymon Plotka; Arleta Adamowicz; Piotr Fudalej; Przemyslaw Korzeniowski; Tomasz Trzcinski; Arkadiusz Sitek (MICCAI (3), 2024)

Task-recency bias strikes back: Adapting covariances in Exemplar-Free Class Incremental Learning. - Grzegorz Rypesc; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski (NeurIPS, 2024)

MISS: Multiclass Interpretable Scoring Systems. - Michal K. Grzeszczyk; Tomasz Trzcinski; Arkadiusz Sitek (SDM, 2024)

Towards More Realistic Membership Inference Attacks on Large Diffusion Models. - Jan Dubinski; Antoni Kowalczuk; Stanislaw Pawlak; Przemyslaw Rokita; Tomasz Trzcinski; Pawel Morawiecki (WACV, 2024)

CLIP-DIY: CLIP Dense Inference Yields Open-Vocabulary Semantic Segmentation For-Free. - Monika Wysoczanska; Michaël Ramamonjisoa; Tomasz Trzcinski; Oriane Siméoni (WACV, 2024)

Looking Through the Past: Better Knowledge Retention for Generative Replay in Continual Learning. - Valeriya Khan; Sebastian Cygert; Kamil Deja; Tomasz Trzcinski; Bartlomiej Twardowski (IEEE Access, 2024)

Toward Unsupervised Visual Reasoning: Do Off-the-Shelf Features Know How to Reason? - Monika Wysoczanska; Tom Monnier; Tomasz Trzcinski; David Picard (IEEE Access, 2024)

GUIDE: Guidance-based Incremental Learning with Diffusion Models. - Bartosz Cywinski; Kamil Deja; Tomasz Trzcinski; Bartlomiej Twardowski; Lukasz Kucinski (CoRR, 2024)

Accelerated Inference and Reduced Forgetting: The Dual Benefits of Early-Exit Networks in Continual Learning. - Filip Szatkowski; Fei Yang 004; Bartlomiej Twardowski; Tomasz Trzcinski; Joost van de Weijer 001 (CoRR, 2024)

A Study of Test-time Contrastive Concepts for Open-world, Open-vocabulary Semantic Segmentation. - Monika Wysoczanska; Antonín Vobecký; Amaia Cardiel; Tomasz Trzcinski; Renaud Marlet; Andrei Bursuc; Oriane Siméoni (CoRR, 2024)

Realistic Evaluation of Test-Time Adaptation Algorithms: Unsupervised Hyperparameter Selection. - Sebastian Cygert; Damian Sójka; Tomasz Trzcinski; Bartlomiej Twardowski (CoRR, 2024)

Joint or Disjoint: Mixing Training Regimes for Early-Exit Models. - Bartlomiej Krzepkowski; Monika Michaluk; Franciszek Szarwacki; Piotr Kubaty; Jary Pomponi; Tomasz Trzcinski; Bartosz Wójcik; Kamil Adamczewski (CoRR, 2024)

LumiGauss: High-Fidelity Outdoor Relighting with 2D Gaussian Splatting. - Joanna Kaleta; Kacper Kania; Tomasz Trzcinski; Marek Kowalski (CoRR, 2024)

Efficient GPU implementation of randomized SVD and its applications. - Lukasz Struski; Pawel M. Morkisz; Przemyslaw Spurek; Samuel Rodriguez Bernabeu; Tomasz Trzcinski (Expert Syst. Appl., 2024)

Points2NeRF: Generating Neural Radiance Fields from 3D point cloud. - Dominik Zimny; Joanna Waczynska; Tomasz Trzcinski; Przemyslaw Spurek (Pattern Recognit. Lett., 2024)

Hypernetworks for image recontextualization. - Maciej Zieba; Jakub Balicki; Tomasz Drózdz; Konrad Karanowski; Pawel Lorek; Hong Lyu; Aleksander Skorupa; Tomasz Trzcinski; Oriol Caudevilla; Jakub M. Tomczak (UniReps, 2025)

LumiGauss: Relightable Gaussian Splatting in the Wild. - Joanna Kaleta; Kacper Kania; Tomasz Trzcinski; Marek Kowalski (WACV, 2025)

Exploring the Stability Gap in Continual Learning: The Role of the Classification Head. - Wojciech Lapacz; Daniel Marczak; Filip Szatkowski; Tomasz Trzcinski (WACV, 2025)

Beyond Grids: Exploring Elastic Input Sampling for Vision Transformers. - Adam Pardyl; Grzegorz Kurzejamski; Jan Olszewski; Tomasz Trzcinski; Bartosz Zielinski 001 (WACV, 2025)

PTFNet: Robotic-Relevant, Single-View Obstacle Footprint Estimation From Sparse and Incomplete Point Clouds. - Konrad P. Cop; Tomasz Trzcinski (IEEE Access, 2025)

Adapt & Align: Continual Learning with Generative Models' Latent Space Alignment. - Kamil Deja; Bartosz Cywinski; Jan Rybarczyk; Tomasz Trzcinski (Neurocomputing, 2025)

Test-time Contrastive Concepts for Open-world Semantic Segmentation with Vision-Language Models. - Monika Wysoczanska; Antonín Vobecký; Amaia Cardiel; Tomasz Trzcinski; Renaud Marlet; Andrei Bursuc; Oriane Siméoni (Trans. Mach. Learn. Res., 2025)

Maybe I Should Not Answer That, but... Do LLMs Understand The Safety of Their Inputs? - Maciej Chrabaszcz; Filip Szatkowski; Bartosz Wójcik; Jan Dubinski; Tomasz Trzcinski (CoRR, 2025)

1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities. - Kevin Wang; Ishaan Javali; Michal Bortkiewicz; Tomasz Trzcinski; Benjamin Eysenbach (CoRR, 2025)

Unpacking Softmax: How Temperature Drives Representation Collapse, Compression, and Generalization. - Wojciech Masarczyk; Mateusz Ostaszewski; Tin Sum Cheng; Tomasz Trzcinski; Aurélien Lucchi; Razvan Pascanu (CoRR, 2025)

Addressing The Devastating Effects Of Single-Task Data Poisoning In Exemplar-Free Continual Learning. - Stanislaw Pawlak; Bartlomiej Twardowski; Tomasz Trzcinski; Joost van de Weijer 001 (CoRR, 2025)