159 citations · 260 across the 8 of their papers we have counts for
9 papers
Benchmarking Composed Image Retrieval for Applied Earth Observation
Bill Psomas, Dionysis Christopoulos, Thanasis Petropoulos +6
Remote sensing composed image retrieval (RSCIR) enables search in large satellite image archives using composed queries that combine a reference image with a textual modifier. Alth…
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Theodoros Kouzelis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Latent generative models have emerged as a leading approach for high-quality image synthesis. These models rely on an autoencoder to compress images into a latent space, followed b…
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Semantic future prediction is important for autonomous systems navigating dynamic environments. This paper introduces FUTURIST, a method for multimodal future semantic prediction t…
DINO-Foresight: Looking into the Future with DINO
Efstathios Karypidis, Ioannis Kakogeorgiou, Spyros Gidaris +1
Predicting future dynamics is crucial for applications like autonomous driving and robotics, where understanding the environment is key. Existing pixel-level methods are computatio…
Composed Image Retrieval for Remote Sensing
Bill Psomas, Ioannis Kakogeorgiou, Nikos Efthymiadis +4
This work introduces composed image retrieval to remote sensing. It allows to query a large image archive by image examples alternated by a textual description, enriching the descr…
SPOT: Self-Training with Patch-Order Permutation for Object-Centric Learning with Autoregressive Transformers
Ioannis Kakogeorgiou, Spyros Gidaris, Konstantinos Karantzalos +1
Unsupervised object-centric learning aims to decompose scenes into interpretable object entities, termed slots. Slot-based auto-encoders stand out as a prominent method for this ta…
Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?
Bill Psomas, Ioannis Kakogeorgiou, Konstantinos Karantzalos +1
Convolutional networks and vision transformers have different forms of pairwise interactions, pooling across layers and pooling at the end of the network. Does the latter really ne…
What to Hide from Your Students: Attention-Guided Masked Image Modeling
Ioannis Kakogeorgiou, Spyros Gidaris, Bill Psomas +4
Transformers and masked language modeling are quickly being adopted and explored in computer vision as vision transformers and masked image modeling (MIM). In this work, we argue t…
Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing
Ioannis Kakogeorgiou, Konstantinos Karantzalos
Although deep neural networks hold the state-of-the-art in several remote sensing tasks, their black-box operation hinders the understanding of their decisions, concealing any bias…