2 citations · 3 across the 12 of their papers we have counts for
14 papers
Fidelity- and Perception-Aware Local Implicit Attention for Arbitrary-Scale Image Super-Resolution
Yu-Syuan Xu, Hao-Lun Sun, Hao-Wei Chen +2
Arbitrary-scale image super-resolution (ASISR) aims to reconstruct high-resolution images from low-resolution inputs over a continuous range of upscaling factors. While traditional…
UniCanvas: A Diffusion-base Unified Model for Text-in-Image Joint Generation
Zeyuan Yang, Hao-Wei Chen, Xueyang Yu +5
Recent years have seen remarkable progress in unified vision-language models handling both multimodal understanding and generation within a single architecture. While autoregressiv…
Landscape-Awareness for Geometric View Diffusion Model
Yan-Ting Chen, Hao-Wei Chen, Tsu-Ching Hsiao +1
Accurate camera viewpoint estimation under sparse-view conditions remains challenging, particularly in two-view scenarios. Recent approaches leverage diffusion models such as Zero1…
All-in-One Medical Image Restoration with Latent Diffusion-Enhanced Vector-Quantized Codebook Prior
Haowei Chen, Zhiwen Yang, Haotian Hou +4
All-in-one medical image restoration (MedIR) aims to address multiple MedIR tasks using a unified model, concurrently recovering various high-quality (HQ) medical images (e.g., MRI…
Parallel Sampling of Diffusion Models on
Yan-Ting Chen, Hao-Wei Chen, Tsu-Ching Hsiao +1
In this paper, we design an algorithm to accelerate the diffusion process on the manifold. The inherently sequential nature of diffusion models necessitates substantial tim…
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Yu-Cheng Lin, Yu-Syuan Xu, Hao-Wei Chen +2
Image restoration is a key task in low-level computer vision that aims to reconstruct high-quality images from degraded inputs. The emergence of Vision Mamba, which draws inspirati…
HoliSDiP: Image Super-Resolution via Holistic Semantics and Diffusion Prior
Li-Yuan Tsao, Hao-Wei Chen, Hao-Wei Chung +4
Text-to-image diffusion models have emerged as powerful priors for real-world image super-resolution (Real-ISR). However, existing methods may produce unintended results due to noi…
Region Attention Transformer for Medical Image Restoration
Zhiwen Yang, Haowei Chen, Ziniu Qian +5
Transformer-based methods have demonstrated impressive results in medical image restoration, attributed to the multi-head self-attention (MSA) mechanism in the spatial dimension. H…
All-In-One Medical Image Restoration via Task-Adaptive Routing
Zhiwen Yang, Haowei Chen, Ziniu Qian +5
Although single-task medical image restoration (MedIR) has witnessed remarkable success, the limited generalizability of these methods poses a substantial obstacle to wider applica…
AdaIR: Exploiting Underlying Similarities of Image Restoration Tasks with Adapters
Hao-Wei Chen, Yu-Syuan Xu, Kelvin C. K. Chan +3
Existing image restoration approaches typically employ extensive networks specifically trained for designated degradations. Despite being effective, such methods inevitably entail…
Boosting Flow-based Generative Super-Resolution Models via Learned Prior
Li-Yuan Tsao, Yi-Chen Lo, Chia-Che Chang +4
Flow-based super-resolution (SR) models have demonstrated astonishing capabilities in generating high-quality images. However, these methods encounter several challenges during ima…
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)
Tsu-Ching Hsiao, Hao-Wei Chen, Hsuan-Kung Yang +1
Addressing pose ambiguity in 6D object pose estimation from single RGB images presents a significant challenge, particularly due to object symmetries or occlusions. In response, we…
Cascaded Local Implicit Transformer for Arbitrary-Scale Super-Resolution
Hao-Wei Chen, Yu-Syuan Xu, Min-Fong Hong +3
Implicit neural representation has recently shown a promising ability in representing images with arbitrary resolutions. In this paper, we present a Local Implicit Transformer (LIT…
Pixel-Wise Prediction based Visual Odometry via Uncertainty Estimation
Hao-Wei Chen, Ting-Hsuan Liao, Hsuan-Kung Yang +1
This paper introduces pixel-wise prediction based visual odometry (PWVO), which is a dense prediction task that evaluates the values of translation and rotation for every pixel in…