5 papers · 1 filter
Step by Step Network
Dongchen Han, Tianzhu Ye, Zhuofan Xia +4
Scaling up network depth is a fundamental pursuit in neural architecture design, as theory suggests that deeper models offer exponentially greater capability. Benefiting from the r…
Task-Aware Image Signal Processor for Advanced Visual Perception
Kai Chen, Jin Xiao, Leheng Zhang +2
In recent years, there has been a growing trend in computer vision towards exploiting RAW sensor data, which preserves richer information compared to conventional low-bit RGB image…
DeNVeR: Deformable Neural Vessel Representations for Unsupervised Video Vessel Segmentation
Chun-Hung Wu, Shih-Hong Chen, Chih-Yao Hu +6
This paper presents Deformable Neural Vessel Representations (DeNVeR), an unsupervised approach for vessel segmentation in X-ray angiography videos without annotated ground truth.…
PatchScaler: An Efficient Patch-Independent Diffusion Model for Image Super-Resolution
Yong Liu, Hang Dong, Jinshan Pan +5
While diffusion models significantly improve the perceptual quality of super-resolved images, they usually require a large number of sampling steps, resulting in high computational…
Navigating Efficiency in MobileViT through Gaussian Process on Global Architecture Factors
Ke Meng, Kai Chen
Numerous techniques have been meticulously designed to achieve optimal architectures for convolutional neural networks (CNNs), yet a comparable focus on vision transformers (ViTs)…