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FARCLUSS: Fuzzy Adaptive Rebalancing and Contrastive Uncertainty Learning for Semi-Supervised Semantic Segmentation
Ebenezer Tarubinga, Jenifer Kalafatovich, Seong-Whan Lee
Semi-supervised semantic segmentation (SSSS) faces persistent challenges in effectively leveraging unlabeled data, such as ineffective utilization of pseudo-labels, exacerbation of…
CW-BASS: Confidence-Weighted Boundary-Aware Learning for Semi-Supervised Semantic Segmentation
Ebenezer Tarubinga, Jenifer Kalafatovich, Seong-Whan Lee
Semi-supervised semantic segmentation (SSSS) aims to improve segmentation performance by utilizing large amounts of unlabeled data with limited labeled samples. Existing methods of…
CanonicalFusion: Generating Drivable 3D Human Avatars from Multiple Images
Jisu Shin, Junmyeong Lee, Seongmin Lee +4
We present a novel framework for reconstructing animatable human avatars from multiple images, termed CanonicalFusion. Our central concept involves integrating individual reconstru…
TIFu: Tri-directional Implicit Function for High-Fidelity 3D Character Reconstruction
Byoungsung Lim, Seong-Whan Lee
Recent advances in implicit function-based approaches have shown promising results in 3D human reconstruction from a single RGB image. However, these methods are not sufficient to…