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Found 38 papers, 15 papers with code
MDN: Mamba-Driven Dualstream Network For Medical Hyperspectral Image Segmentation
Medical Hyperspectral Imaging (MHSI) offers potential for computational pathology and precision medicine.
Progressive Vision-Language Prompt for Multi-Organ Multi-Class Cell Semantic Segmentation with Single Branch
Given that multiple cell types exist across various organs, with subtle differences in cell size and shape, multi-organ, multi-class cell segmentation is particularly challenging.
A Semi-Supervised Approach with Error Reflection for Echocardiography Segmentation
The first step is called reconstruction reflection.
Label Filling via Mixed Supervision for Medical Image Segmentation from Noisy Annotations
The fundamental idea of label filling is to supervise the segmentation model by a subset of pixels with trustworthy labels, meanwhile filling labels of other pixels by mixed supervision.
RefineStyle: Dynamic Convolution Refinement for StyleGAN
In StyleGAN, convolution kernels are shaped by both static parameters shared across images and dynamic modulation factors $w^+\in\mathcal{W}^+$ specific to each image.
Boosting Open-Domain Continual Learning via Leveraging Intra-domain Category-aware Prototype
Despite recent progress in enhancing the efficacy of Open-Domain Continual Learning (ODCL) in Vision-Language Models (VLM), failing to (1) correctly identify the Task-ID of a test image and (2) use only the category set corresponding to the Task-ID, while preserving the knowledge related to each domain, cannot address the two primary challenges of ODCL: forgetting old knowledge and maintaining zero-shot capabilities, as well as the confusions caused by category-relatedness between domains.
LoFormer: Local Frequency Transformer for Image Deblurring
Due to the computational complexity of self-attention (SA), prevalent techniques for image deblurring often resort to either adopting localized SA or employing coarse-grained global SA methods, both of which exhibit drawbacks such as compromising global modeling or lacking fine-grained correlation.
Ranked #3 on
Image Deblurring
on GoPro
Spatially-Variant Degradation Model for Dataset-free Super-resolution
Unlike existing dataset-free BISR methods that focus on obtaining a degradation kernel for the entire image, we are the first to explicitly design a spatially-variant degradation model for each pixel.
Prompting Whole Slide Image Based Genetic Biomarker Prediction
Experimental results on two colorectal cancer datasets show the superiority of our method, achieving 91. 49% in AUC for MSI classification.
AdaRevD: Adaptive Patch Exiting Reversible Decoder Pushes the Limit of Image Deblurring
Despite the recent progress in enhancing the efficacy of image deblurring, the limited decoding capability constrains the upper limit of State-Of-The-Art (SOTA) methods.
Ranked #1 on
Image Deblurring
on GoPro
OD-DETR: Online Distillation for Stabilizing Training of Detection Transformer
First, the matching relation between object queries and ground truth (GT) boxes in the teacher is employed to guide the student, so queries within the student are not only assigned labels based on their own predictions, but also refer to the matching results from the teacher.
I$^3$Net: Inter-Intra-slice Interpolation Network for Medical Slice Synthesis
Based on this observation, we propose an Inter-Intra-slice Interpolation Network (I$^3$Net), which fully explores information from high in-plane resolution and compensates for low through-plane resolution.
DSAM-GN:Graph Network based on Dynamic Similarity Adjacency Matrices for Vehicle Re-identification
Finally, the nodes and similarity adjacency matrices are fed into graph networks to extract more discriminative features for vehicle Re-ID.
Gene-induced Multimodal Pre-training for Image-omic Classification
Histology analysis of the tumor micro-environment integrated with genomic assays is the gold standard for most cancers in modern medicine.
Atrial Septal Defect Detection in Children Based on Ultrasound Video Using Multiple Instances Learning
In addition, data from 30 children patients (15 positives and 15 negatives) are collected for clinician testing and compared to our model test results (these 30 samples do not participate in model training).
Bidirectional Copy-Paste for Semi-Supervised Medical Image Segmentation
In semi-supervised medical image segmentation, there exist empirical mismatch problems between labeled and unlabeled data distribution.
Image Segmentation
Semi-supervised Medical Image Segmentation
+1
EDMAE: An Efficient Decoupled Masked Autoencoder for Standard View Identification in Pediatric Echocardiography
The EDMAE encoder is composed of a teacher and a student encoder.
Class Balanced Adaptive Pseudo Labeling for Federated Semi-Supervised Learning
The second key element is that we design class balanced adaptive thresholds via considering the empirical distribution of all training data in local clients, to encourage a balanced training process.
MagicNet: Semi-Supervised Multi-Organ Segmentation via Magic-Cube Partition and Recovery
Our strategy encourages unlabeled images to learn organ semantics in relative locations from the labeled images (cross-branch) and enhances the learning ability for small organs (within-branch).
CLIP-ReID: Exploiting Vision-Language Model for Image Re-Identification without Concrete Text Labels
The key idea is to fully exploit the cross-modal description ability in CLIP through a set of learnable text tokens for each ID and give them to the text encoder to form ambiguous descriptions.
Ranked #1 on
Person Re-Identification
on MSMT17
IoU-Enhanced Attention for End-to-End Task Specific Object Detection
Without densely tiled anchor boxes or grid points in the image, sparse R-CNN achieves promising results through a set of object queries and proposal boxes updated in the cascaded training manner.
S$^3$R: Self-supervised Spectral Regression for Hyperspectral Histopathology Image Classification
More concretely, we propose to learn a set of linear coefficients that can be used to represent one band by the remaining bands via masking out these bands.
Cross Attention Based Style Distribution for Controllable Person Image Synthesis
In this paper, we propose a cross attention based style distribution module that computes between the source semantic styles and target pose for pose transfer.
QS-Attn: Query-Selected Attention for Contrastive Learning in I2I Translation
By constraining features from the same location to be closer than those from different ones, it implicitly ensures the result to take content from the source.
Style Transformer for Image Inversion and Editing
Existing GAN inversion methods fail to provide latent codes for reliable reconstruction and flexible editing simultaneously.
Intriguing Findings of Frequency Selection for Image Deblurring
Blur was naturally analyzed in the frequency domain, by estimating the latent sharp image and the blur kernel given a blurry image.
Ranked #5 on
Deblurring
on RealBlur-R (trained on GoPro)
Bridging the Gap between Label- and Reference-based Synthesis in Multi-attribute Image-to-Image Translation
The two types of synthesis, either label- or reference-based, have substantial differences.
LSC-GAN: Latent Style Code Modeling for Continuous Image-to-image Translation
Image-to-image (I2I) translation is usually carried out among discrete domains.
Angel's Girl for Blind Painters: an Efficient Painting Navigation System Validated by Multimodal Evaluation Approach
This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands.
SpecTr: Spectral Transformer for Hyperspectral Pathology Image Segmentation
Hyperspectral imaging (HSI) unlocks the huge potential to a wide variety of applications relied on high-precision pathology image segmentation, such as computational pathology and precision medicine.
ID-Unet: Iterative Soft and Hard Deformation for View Synthesis
View synthesis is usually done by an autoencoder, in which the encoder maps a source view image into a latent content code, and the decoder transforms it into a target view image according to the condition.
Claw U-Net: A Unet-based Network with Deep Feature Concatenation for Scleral Blood Vessel Segmentation
Sturge-Weber syndrome (SWS) is a vascular malformation disease, and it may cause blindness if the patient's condition is severe.
Identification of deep breath while moving forward based on multiple body regions and graph signal analysis
This paper presents an unobtrusive solution that can automatically identify deep breath when a person is walking past the global depth camera.
Face Mask Assistant: Detection of Face Mask Service Stage Based on Mobile Phone
Aimed at solving the problem that we don't know which service stage of the mask belongs to, we propose a detection system based on the mobile phone.
Novel View Synthesis on Unpaired Data by Conditional Deformable Variational Auto-Encoder
Novel view synthesis often needs the paired data from both the source and target views.
Abnormal respiratory patterns classifier may contribute to large-scale screening of people infected with COVID-19 in an accurate and unobtrusive manner
During the epidemic prevention and control period, our study can be helpful in prognosis, diagnosis and screening for the patients infected with COVID-19 (the novel coronavirus) based on breathing characteristics.
Disentangling the Spatial Structure and Style in Conditional VAE
Depending on whether the label is related with the spatial structure, the output $z_s$ from the condition mapping network is used either as a style code or a spatial structure code.
