Zobrazeno 1 - 10
of 282
pro vyhledávání: '"Liu, Anan"'
Autor:
Zhang, Xuanpu, Song, Dan, Zhan, Pengxin, Chang, Tianyu, Zeng, Jianhao, Chen, Qingguo, Luo, Weihua, Liu, Anan
Image-based virtual try-on is an increasingly popular and important task to generate realistic try-on images of the specific person. Recent methods model virtual try-on as image mask-inpaint task, which requires masking the person image and results i
Externí odkaz:
http://arxiv.org/abs/2408.06047
Generative Adversarial Networks (GANs) dominate the research field in image-based virtual try-on, but have not resolved problems such as unnatural deformation of garments and the blurry generation quality. While the generative quality of diffusion mo
Externí odkaz:
http://arxiv.org/abs/2311.18405
Autor:
Song, Dan, Fu, Xinwei, Liu, Ning, Nie, Weizhi, Li, Wenhui, Wang, Lanjun, Yang, You, Liu, Anan
Large-scale pre-trained models have demonstrated impressive performance in vision and language tasks within open-world scenarios. Due to the lack of comparable pre-trained models for 3D shapes, recent methods utilize language-image pre-training to re
Externí odkaz:
http://arxiv.org/abs/2311.18402
Social platforms such as Twitter are under siege from a multitude of fraudulent users. In response, social bot detection tasks have been developed to identify such fake users. Due to the structure of social networks, the majority of methods are based
Externí odkaz:
http://arxiv.org/abs/2310.07159
Emotion detection is a critical technology extensively employed in diverse fields. While the incorporation of commonsense knowledge has proven beneficial for existing emotion detection methods, dialogue-based emotion detection encounters numerous dif
Externí odkaz:
http://arxiv.org/abs/2309.06928
With the development of deep learning techniques, supervised learning has achieved performances surpassing those of humans. Researchers have designed numerous corresponding models for different data modalities, achieving excellent results in supervis
Externí odkaz:
http://arxiv.org/abs/2308.13801
The chest X-ray is often utilized for diagnosing common thoracic diseases. In recent years, many approaches have been proposed to handle the problem of automatic diagnosis based on chest X-rays. However, the scarcity of labeled data for related disea
Externí odkaz:
http://arxiv.org/abs/2306.01232
The chest X-ray (CXR) is one of the most common and easy-to-get medical tests used to diagnose common diseases of the chest. Recently, many deep learning-based methods have been proposed that are capable of effectively classifying CXRs. Even though t
Externí odkaz:
http://arxiv.org/abs/2305.12072
The chest X-ray (CXR) is commonly employed to diagnose thoracic illnesses, but the challenge of achieving accurate automatic diagnosis through this method persists due to the complex relationship between pathology. In recent years, various deep learn
Externí odkaz:
http://arxiv.org/abs/2305.12070
We synthesized a pure organic non-metal crystalline covalent organic framework TAPA-BTD-COF by bottom-up Schiff base chemical reaction. And this imine-based COF is stable in aerobic condition and room-temperature. We discovered that this TAPA-BTD-COF
Externí odkaz:
http://arxiv.org/abs/2205.07541