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Found 24 papers, 12 papers with code
FreeCam3D: Snapshot Structured Light 3D with Freely-Moving Cameras
The projected pattern can be observed in part or full by any camera, to reconstruct both the 3D map of the scene and the camera pose in the projector coordinates.
CodeBrain: Impute Any Brain MRI via Instance-specific Scalar-quantized Codes
To this end, CodeBrain is trained in two stages: Reconstruction and Code Prediction.
Cycle-Consistent Bridge Diffusion Model for Accelerated MRI Reconstruction
CBDM employs two bridge diffusion models to construct a cycle-consistent diffusion process with a consistency loss, enhancing the fine-grained details of reconstructed images and reducing the number of diffusion steps.
Cross Group Attention and Group-wise Rolling for Multimodal Medical Image Synthesis
Multimodal MR image synthesis aims to generate missing modality image by fusing and mapping a few available MRI data.
Diversified and Personalized Multi-rater Medical Image Segmentation
To address it, the common practice is to gather multiple annotations from different experts, leading to the setting of multi-rater medical image segmentation.
Segment Together: A Versatile Paradigm for Semi-Supervised Medical Image Segmentation
Therefore, in this paper, we introduce a \textbf{Ver}satile \textbf{Semi}-supervised framework (VerSemi) to point out a new perspective that integrates various tasks into a unified model with a broad label space, to exploit more unlabeled data for semi-supervised medical image segmentation.
CoactSeg: Learning from Heterogeneous Data for New Multiple Sclerosis Lesion Segmentation
Moreover, a simple and effective relation regularization is proposed to ensure the longitudinal relations among the three outputs to improve the model learning.
Universal Semi-Supervised Learning for Medical Image Classification
However, in practical scenarios, unlabeled data would be from unseen classes or unseen domains, and it is still challenging to exploit them by existing SSL methods.
Reliability-Adaptive Consistency Regularization for Weakly-Supervised Point Cloud Segmentation
Weakly-supervised point cloud segmentation with extremely limited labels is highly desirable to alleviate the expensive costs of collecting densely annotated 3D points.
Energy-Efficient Adaptive 3D Sensing
Active depth sensing achieves robust depth estimation but is usually limited by the sensing range.
Privacy-Preserving Visual Localization with Event Cameras
We present a robust, privacy-preserving visual localization algorithm using event cameras.
Seeing Far in the Dark with Patterned Flash
Flash illumination is widely used in imaging under low-light environments.
Dual Adaptive Transformations for Weakly Supervised Point Cloud Segmentation
Weakly supervised point cloud segmentation, i. e. semantically segmenting a point cloud with only a few labeled points in the whole 3D scene, is highly desirable due to the heavy burden of collecting abundant dense annotations for the model training.
Structured Light with Redundancy Codes
We propose three applications using our redundancy codes: (1) Self error-correction for SL imaging under strong ambient light, (2) Error detection for adaptive reconstruction under global illumination, and (3) Interference filtering with device-specific projection sequence encoding, especially for event camera-based SL and light curtain devices.
Flexible Sampling for Long-tailed Skin Lesion Classification
To address this, in this paper, we propose a curriculum learning-based framework called Flexible Sampling for the long-tailed skin lesion classification task.
Exploring Smoothness and Class-Separation for Semi-supervised Medical Image Segmentation
The pixel-level smoothness forces the model to generate invariant results under adversarial perturbations.
ProposalCLIP: Unsupervised Open-Category Object Proposal Generation via Exploiting CLIP Cues
Firstly, we analyze CLIP for unsupervised open-category proposal generation and design an objectness score based on our empirical analysis on proposal selection.
3D Photo Stylization: Learning to Generate Stylized Novel Views from a Single Image
Our key intuition is that style transfer and view synthesis have to be jointly modeled for this task.
Mutual Consistency Learning for Semi-supervised Medical Image Segmentation
In this paper, we propose a novel mutual consistency network (MC-Net+) to effectively exploit the unlabeled data for semi-supervised medical image segmentation.
CodedStereo: Learned Phase Masks for Large Depth-of-field Stereo
Conventional stereo suffers from a fundamental trade-off between imaging volume and signal-to-noise ratio (SNR) -- due to the conflicting impact of aperture size on both these variables.
Semi-supervised Left Atrium Segmentation with Mutual Consistency Training
Such mutual consistency encourages the two decoders to have consistent and low-entropy predictions and enables the model to gradually capture generalized features from these unlabeled challenging regions.
How to Train Neural Networks for Flare Removal
When a camera is pointed at a strong light source, the resulting photograph may contain lens flare artifacts.
Rethinking the Extraction and Interaction of Multi-Scale Features for Vessel Segmentation
Analyzing the morphological attributes of blood vessels plays a critical role in the computer-aided diagnosis of many cardiovascular and ophthalmologic diseases.
PhaseCam3D — Learning Phase Masks for Passive Single View Depth Estimation
Multi-camera systems provide state of the art performance for passive 3D imaging.
