{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T02:32:04Z","timestamp":1778812324854,"version":"3.51.4"},"reference-count":0,"publisher":"Association for the Advancement of Artificial Intelligence (AAAI)","issue":"01","license":[{"start":{"date-parts":[[2019,7,17]],"date-time":"2019-07-17T00:00:00Z","timestamp":1563321600000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.aaai.org"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AAAI"],"abstract":"<jats:p>Generating photo-realistic images conditioned on semantic text descriptions is a challenging task in computer vision field. Due to the nature of hierarchical representations learned in CNN, it is intuitive to utilize richer convolutional features to improve text-to-image synthesis. In this paper, we propose Perceptual Pyramid Adversarial Network (PPAN) to directly synthesize multi-scale images conditioned on texts in an adversarial way. Specifically, we design one pyramid generator and three independent discriminators to synthesize and regularize multi-scale photo-realistic images in one feed-forward process. At each pyramid level, our method takes coarse-resolution features as input, synthesizes highresolution images, and uses convolutions for up-sampling to finer level. Furthermore, the generator adopts the perceptual loss to enforce semantic similarity between the synthesized image and the ground truth, while a multi-purpose discriminator encourages semantic consistency, image fidelity and class invariance. Experimental results show that our PPAN sets new records for text-to-image synthesis on two benchmark datasets: CUB (i.e., 4.38 Inception Score and .290 Visual-semantic Similarity) and Oxford-102 (i.e., 3.52 Inception Score and .297 Visual-semantic Similarity).<\/jats:p>","DOI":"10.1609\/aaai.v33i01.33018312","type":"journal-article","created":{"date-parts":[[2019,8,21]],"date-time":"2019-08-21T07:45:47Z","timestamp":1566373547000},"page":"8312-8319","source":"Crossref","is-referenced-by-count":30,"title":["Perceptual Pyramid Adversarial Networks for Text-to-Image Synthesis"],"prefix":"10.1609","volume":"33","author":[{"given":"Lianli","family":"Gao","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Daiyuan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingkuan","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xing","family":"Xu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongxiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Heng Tao","family":"Shen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"9382","published-online":{"date-parts":[[2019,7,17]]},"container-title":["Proceedings of the AAAI Conference on Artificial Intelligence"],"original-title":[],"link":[{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/4844\/4717","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/download\/4844\/4717","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,7]],"date-time":"2022-11-07T06:49:17Z","timestamp":1667803757000},"score":1,"resource":{"primary":{"URL":"https:\/\/ojs.aaai.org\/index.php\/AAAI\/article\/view\/4844"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,17]]},"references-count":0,"journal-issue":{"issue":"01","published-online":{"date-parts":[[2019,7,23]]}},"URL":"https:\/\/doi.org\/10.1609\/aaai.v33i01.33018312","relation":{},"ISSN":["2374-3468","2159-5399"],"issn-type":[{"value":"2374-3468","type":"electronic"},{"value":"2159-5399","type":"print"}],"subject":[],"published":{"date-parts":[[2019,7,17]]}}}