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Found 9 papers, 7 papers with code
EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
Latent generative models have emerged as a leading approach for high-quality image synthesis.
Advancing Semantic Future Prediction through Multimodal Visual Sequence Transformers
Our approach incorporates a multimodal masked visual modeling objective and a novel masking mechanism designed for multimodal training.
$\texttt{DINO-Foresight}$: Looking into the Future with DINO
Our approach trains a masked feature transformer in a self-supervised manner to predict the evolution of VFM features over time.
Composed Image Retrieval for Remote Sensing
Various attributes can be modified by the textual part, such as shape, color, or context.
Keep It SimPool: Who Said Supervised Transformers Suffer from Attention Deficit?
By discussing the properties of each group of methods, we derive SimPool, a simple attention-based pooling mechanism as a replacement of the default one for both convolutional and transformer encoders.
What to Hide from Your Students: Attention-Guided Masked Image Modeling
In this work, we argue that image token masking differs from token masking in text, due to the amount and correlation of tokens in an image.
MARIDA: A benchmark for Marine Debris detection from Sentinel-2 remote sensing data
Currently, a significant amount of research is focused on detecting Marine Debris and assessing its spectral behaviour via remote sensing, ultimately aiming at new operational monitoring solutions.
Ranked #2 on
Image Segmentation
on MARIDA
Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing
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 and other shortcomings in datasets and model performance.
Explainable artificial intelligence
Explainable Artificial Intelligence (XAI)
+2
