Search Results for author:
Found 9 papers, 2 papers with code
T-Mamba: Frequency-Enhanced Gated Long-Range Dependency for Tooth 3D CBCT Segmentation
To address this issue, we propose T-Mamba, integrating shared positional encoding and frequency-based features into vision mamba, to address limitations in spatial position preservation and feature enhancement in frequency domain.
GEM: Boost Simple Network for Glass Surface Segmentation via Segment Anything Model and Data Synthesis
To segment glass surfaces with higher accuracy, we make full use of two visual foundation models: Segment Anything (SAM) and Stable Diffusion. Specifically, we devise a simple glass surface segmentor named GEM, which only consists of a SAM backbone, a simple feature pyramid, a discerning query selection module, and a mask decoder.
Heterogeneous Generative Knowledge Distillation with Masked Image Modeling
Masked image modeling (MIM) methods achieve great success in various visual tasks but remain largely unexplored in knowledge distillation for heterogeneous deep models.
A Stronger Stitching Algorithm for Fisheye Images based on Deblurring and Registration
However, the fisheye image has a severe geometric distortion which may interfere with the stage of image registration and stitching.
Simple parameter-free self-attention approximation
The hybrid model of self-attention and convolution is one of the methods to lighten ViT.
Language-aware Multiple Datasets Detection Pretraining for DETRs
Pretraining on large-scale datasets can boost the performance of object detectors while the annotated datasets for object detection are hard to scale up due to the high labor cost.
A Lightweight and Accurate Recognition Framework for Signs of X-ray Weld Images
Based on SCE module, a narrow network is designed for final weld information recognition.
TransForensics: Image Forgery Localization with Dense Self-Attention
Nowadays advanced image editing tools and technical skills produce tampered images more realistically, which can easily evade image forensic systems and make authenticity verification of images more difficult.
An End-to-End Audio Classification System based on Raw Waveforms and Mix-Training Strategy
This paper introduces an end-to-end audio classification system based on raw waveforms and mix-training strategy.
