20 papers
TRUST: Test-Time Refinement using Uncertainty-Guided SSM Traverses
Sahar Dastani, Ali Bahri, Gustavo Adolfo Vargas Hakim +7
State Space Models (SSMs) have emerged as efficient alternatives to Vision Transformers (ViTs), with VMamba standing out as a pioneering architecture designed for vision tasks. How…
Locality-Attending Vision Transformer
Sina Hajimiri, Farzad Beizaee, Fereshteh Shakeri +3
Vision transformers have demonstrated remarkable success in classification by leveraging global self-attention to capture long-range dependencies. However, this same mechanism can…
THUNDER: Tile-level Histopathology image UNDERstanding benchmark
Pierre Marza, Leo Fillioux, Sofiène Boutaj +6
Progress in a research field can be hard to assess, in particular when many concurrent methods are proposed in a short period of time. This is the case in digital pathology, where…
OCTOPUS: Enhancing the Spatial-Awareness of Vision SSMs with Multi-Dimensional Scans and Traversal Selection
Kunal Mahatha, Ali Bahri, Pierre Marza +5
State space models (SSMs) have recently emerged as an alternative to transformers due to their unique ability of modeling global relationships in text with linear complexity. Howev…
SPARK: Stochastic Propagation via Affinity-guided Random walK for training-free unsupervised segmentation
Kunal Mahatha, Jose Dolz, Christian Desrosiers
We argue that existing training-free segmentation methods rely on an implicit and limiting assumption, that segmentation is a spectral graph partitioning problem over diffusion-der…
Histopath-C: Towards Realistic Domain Shifts for Histopathology Vision-Language Adaptation
Mehrdad Noori, Gustavo Adolfo Vargas Hakim, David Osowiechi +6
Medical Vision-language models (VLMs) have shown remarkable performances in various medical imaging domains such as histo\-pathology by leveraging pre-trained, contrastive models t…