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Found 11 papers, 2 papers with code
NOVA-3D: Non-overlapped Views for 3D Anime Character Reconstruction
However, there is currently a lack of automated approaches for generating anime characters directly from these 2D designs.
RemoCap: Disentangled Representation Learning for Motion Capture
Reconstructing 3D human bodies from realistic motion sequences remains a challenge due to pervasive and complex occlusions.
Gaussian Control with Hierarchical Semantic Graphs in 3D Human Recovery
Although 3D Gaussian Splatting (3DGS) has recently made progress in 3D human reconstruction, it primarily relies on 2D pixel-level supervision, overlooking the geometric complexity and topological relationships of different body parts.
PE-MED: Prompt Enhancement for Interactive Medical Image Segmentation
It can prevent the highly unfavorable scenarios, such as encountering a blank mask as the initial input after the first interaction.
OnUVS: Online Feature Decoupling Framework for High-Fidelity Ultrasound Video Synthesis
Second, to better preserve the integrity and textural information of US images, we implemented a dual-decoder that decouples the content and textural features in the generator.
Inflated 3D Convolution-Transformer for Weakly-supervised Carotid Stenosis Grading with Ultrasound Videos
First, to avoid the requirement of laborious and unreliable annotation, we propose a novel and effective video classification network for weakly-supervised CSG.
Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification
Second, we introduce a regularization technique that utilizes style interpolation consistency in the frequency space to encourage self-consistency in the logit space of the model output.
Segment Anything Model for Medical Images?
To fully validate SAM's performance on medical data, we collected and sorted 53 open-source datasets and built a large medical segmentation dataset with 18 modalities, 84 objects, 125 object-modality paired targets, 1050K 2D images, and 6033K masks.
Fine-grained Correlation Loss for Regression
In this work, we propose to revisit the classic regression tasks with novel investigations on directly optimizing the fine-grained correlation losses.
Online Reflective Learning for Robust Medical Image Segmentation
Deep segmentation models often face the failure risks when the testing image presents unseen distributions.
Weakly-supervised High-fidelity Ultrasound Video Synthesis with Feature Decoupling
First, leveraging the advantages of self- and fully-supervised learning, our proposed system is trained in weakly-supervised manner for keypoint detection.
