Suchergebnisse - "Deep learning architectures and techniques; Segmentation"

TopFormer: Token Pyramid Transformer for Mobile Semantic Segmentation von Zhang, Wenqiang, Huang, Zilong, Luo, Guozhong, Chen, Tao, Wang, Xinggang, Liu, Wenyu, Yu, Gang, Shen, Chunhua

“… Although vision transformers (ViTs) have achieved great success in computer vision, the heavy computational cost hampers their applications to dense prediction …”
Volltext

Learning What Not to Segment: A New Perspective on Few-Shot Segmentation von Lang, Chunbo, Cheng, Gong, Tu, Binfei, Han, Junwei

“… Recently few-shot segmentation (FSS) has been extensively developed. Most previous works strive to achieve generalization through the meta-learning framework …”
Volltext

Segment, Magnify and Reiterate: Detecting Camouflaged Objects the Hard Way von Jia, Qi, Yao, Shuilian, Liu, Yu, Fan, Xin, Liu, Risheng, Luo, Zhongxuan

“… It is challenging to accurately detect camouflaged objects from their highly similar surroundings. Existing methods mainly leverage a single-stage detection …”
Volltext

PolyWorld: Polygonal Building Extraction with Graph Neural Networks in Satellite Images von Zorzi, Stefano, Bazrafkan, Shabab, Habenschuss, Stefan, Fraundorfer, Friedrich

“… While most state-of-the-art instance segmentation methods produce binary segmentation masks, geographic and cartographic applications typically require precise …”
Volltext

Deep orientation-aware functional maps: Tackling symmetry issues in Shape Matching von Donati, Nicolas, Corman, Etienne, Ovsjanikov, Maks

“… State-of-the-art fully intrinsic network for non-rigid shape matching are unable to disambiguate between shape inner symmetries. Meanwhile, recent advances in …”
Volltext

BoxeR: Box-Attention for 2D and 3D Transformers von Nguyen, Duy-Kien, Ju, Jihong, Booij, Olaf, Oswald, Martin R., Snoek, Cees G. M.

“… In this paper, we propose a simple attention mechanism, we call Box-Attention. It enables spatial interaction between grid features, as sampled from boxes of …”
Volltext

Vox2Cortex: Fast Explicit Reconstruction of Cortical Surfaces from 3D MRI Scans with Geometric Deep Neural Networks von Bongratz, Fabian, Rickmann, Anne-Marie, Polsterl, Sebastian, Wachinger, Christian

“… The reconstruction of cortical surfaces from brain magnetic resonance imaging (MRI) scans is essential for quantitative analyses of cortical thickness and …”
Volltext

Generalizing Interactive Backpropagating Refinement for Dense Prediction Networks von Lin, Fanqing, Price, Brian, Martinez, Tony

“… As deep neural networks become the state-of-the-art approach in the field of computer vision for dense prediction tasks, many methods have been developed for …”
Volltext