Zobrazeno 1 - 10
of 225
pro vyhledávání: '"Yin, Xuesong"'
Image restoration models often face the simultaneous interaction of multiple degradations in real-world scenarios. Existing approaches typically handle single or composite degradations based on scene descriptors derived from text or image embeddings.
Externí odkaz:
http://arxiv.org/abs/2411.10708
This paper proposes the first pure Transformer structure inversion network called SwinStyleformer, which can compensate for the shortcomings of the CNNs inversion framework by handling long-range dependencies and learning the global structure of obje
Externí odkaz:
http://arxiv.org/abs/2406.13153
There are many excellent solutions in image restoration.However, most methods require on training separate models to restore images with different types of degradation.Although existing all-in-one models effectively address multiple types of degradat
Externí odkaz:
http://arxiv.org/abs/2406.12587
Autor:
Made, Riko I, Lin, Jing, Zhang, Jintao, Zhang, Yu, Moh, Lionel C. H., Liu, Zhaolin, Ding, Ning, Chiam, Sing Yang, Khoo, Edwin, Yin, Xuesong, Zheng, Guangyuan Wesley
Publikováno v:
iScience (2024)
Battery health assessment and recuperation play a crucial role in the utilization of second-life Li-ion batteries. However, due to ambiguous aging mechanisms and lack of correlations between the recovery effects and operational states, it is challeng
Externí odkaz:
http://arxiv.org/abs/2310.03750
Electric vehicles (EVs) have become a popular mode of transportation, with their performance depending on the ageing of the Li-ion batteries used to power them. However, it can be challenging and time-consuming to determine the capacity retention of
Externí odkaz:
http://arxiv.org/abs/2309.12191
Masked autoencoders (MAEs) have displayed significant potential in the classification and semantic segmentation of medical images in the last year. Due to the high similarity of human tissues, even slight changes in medical images may represent disea
Externí odkaz:
http://arxiv.org/abs/2305.05871
Compared to other severe weather image restoration tasks, single image desnowing is a more challenging task. This is mainly due to the diversity and irregularity of snow shape, which makes it extremely difficult to restore images in snowy scenes. Mor
Externí odkaz:
http://arxiv.org/abs/2303.09988
Facial expression recognition (FER) plays an important role in a variety of real-world applications such as human-computer interaction. POSTER achieves the state-of-the-art (SOTA) performance in FER by effectively combining facial landmark and image
Externí odkaz:
http://arxiv.org/abs/2301.12149
Vision Transformers (ViTs) outperforms convolutional neural networks (CNNs) in several vision tasks with its global modeling capabilities. However, ViT lacks the inductive bias inherent to convolution making it require a large amount of data for trai
Externí odkaz:
http://arxiv.org/abs/2212.05677
Facial expression recognition (FER) plays a significant role in the ubiquitous application of computer vision. We revisit this problem with a new perspective on whether it can acquire useful representations that improve FER performance in the image g
Externí odkaz:
http://arxiv.org/abs/2211.13564