Search Results for author:
Found 13 papers, 8 papers with code
O-PRESS: Boosting OCT axial resolution with Prior guidance, Recurrence, and Equivariant Self-Supervision
Optical coherence tomography (OCT) is a noninvasive technology that enables real-time imaging of tissue microanatomies.
Supervised Domain Adaptation for Recognizing Retinal Diseases from Wide-Field Fundus Images
This paper addresses the emerging task of recognizing multiple retinal diseases from wide-field (WF) and ultra-wide-field (UWF) fundus images.
Dynamic Video Frame Interpolation with integrated Difficulty Pre-Assessment
Extensive experiments show that easy samples pass through fast models while difficult samples inference with heavy models, and our proposed pipeline can improve the accuracy-efficiency trade-off for VFI.
Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolation
In this paper, we propose a novel module to explicitly extract motion and appearance information via a unifying operation.
Ranked #1 on
Video Frame Interpolation
on MSU Video Frame Interpolation
(PSNR metric)
A Unified Pyramid Recurrent Network for Video Frame Interpolation
Cast in a flexible pyramid framework, UPR-Net exploits lightweight recurrent modules for both bi-directional flow estimation and intermediate frame synthesis.
Ranked #2 on
Video Frame Interpolation
on MSU Video Frame Interpolation
(PSNR metric)
Enhanced Bi-directional Motion Estimation for Video Frame Interpolation
We present a novel simple yet effective algorithm for motion-based video frame interpolation.
Ranked #3 on
Video Frame Interpolation
on MSU Video Frame Interpolation
(LPIPS metric)
APP-Net: Auxiliary-point-based Push and Pull Operations for Efficient Point Cloud Classification
In the existing work, each point in the cloud may inevitably be selected as the neighbors of multiple aggregation centers, as all centers will gather neighbor features from the whole point cloud independently.
Ranked #43 on
3D Point Cloud Classification
on ScanObjectNN
Lesion Localization in OCT by Semi-Supervised Object Detection
Over 300 million people worldwide are affected by various retinal diseases.
Multi-Modal Multi-Instance Learning for Retinal Disease Recognition
We propose in this paper Multi-Modal Multi-Instance Learning (MM-MIL) for selectively fusing CFP and OCT modalities.
ICAF: Iterative Contrastive Alignment Framework for Multimodal Abstractive Summarization
Integrating multimodal knowledge for abstractive summarization task is a work-in-progress research area, with present techniques inheriting fusion-then-generation paradigm.
Learning Two-Stream CNN for Multi-Modal Age-related Macular Degeneration Categorization
Our MM-CNN is instantiated by a two-stream CNN, with spatially-invariant fusion to combine information from the CFP and OCT streams.
Learn to Segment Retinal Lesions and Beyond
This paper attacks the three challenges in the context of diabetic retinopathy (DR) grading.
Two-Stream CNN with Loose Pair Training for Multi-modal AMD Categorization
The CNN's fusion layer is tailored to the need of fusing information from the fundus and OCT streams.
