activity
20162024
most citedBuilt-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation

29 citations · 42 across the 8 of their papers we have counts for

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5 papers · 1 filter

cs.CV2024

Backpropagation-free Network for 3D Test-time Adaptation

Yanshuo Wang, Ali Cheraghian, Zeeshan Hayder +7

Real-world systems often encounter new data over time, which leads to experiencing target domain shifts. Existing Test-Time Adaptation (TTA) methods tend to apply computationally h…

cs.CV2023

Automatic Illumination Spectrum Recovery

Nariman Habili, Jeremy Oorloff, Lars Petersson

We develop a deep learning network to estimate the illumination spectrum of hyperspectral images under various lighting conditions. To this end, a dataset, IllumNet, was created. I…

cs.CV2022

Curved Geometric Networks for Visual Anomaly Recognition

Jie Hong, Pengfei Fang, Weihao Li +3

Learning a latent embedding to understand the underlying nature of data distribution is often formulated in Euclidean spaces with zero curvature. However, the success of the geomet…

cs.CV201613 cited

Deep Action- and Context-Aware Sequence Learning for Activity Recognition and Anticipation

Mohammad Sadegh Aliakbarian, Fatemehsadat Saleh, Basura Fernando +3

Action recognition and anticipation are key to the success of many computer vision applications. Existing methods can roughly be grouped into those that extract global, context-awa…

cs.CV201629 cited

Built-in Foreground/Background Prior for Weakly-Supervised Semantic Segmentation

Fatemehsadat Saleh, Mohammad Sadegh Ali Akbarian, Mathieu Salzmann +3

Pixel-level annotations are expensive and time consuming to obtain. Hence, weak supervision using only image tags could have a significant impact in semantic segmentation. Recently…