Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Faieta, Baldo"'
Autor:
Aggarwal, Pranav, Ravi, Hareesh, Marri, Naveen, Kelkar, Sachin, Chen, Fengbin, Khuc, Vinh, Harikumar, Midhun, Tambi, Ritiz, Kakumanu, Sudharshan Reddy, Lapsiya, Purvak, Ghouas, Alvin, Saber, Sarah, Ramprasad, Malavika, Faieta, Baldo, Kale, Ajinkya
Denoising Diffusion models have shown remarkable performance in generating diverse, high quality images from text. Numerous techniques have been proposed on top of or in alignment with models like Stable Diffusion and Imagen that generate images dire
Externí odkaz:
http://arxiv.org/abs/2302.11710
We present HyperNST; a neural style transfer (NST) technique for the artistic stylization of images, based on Hyper-networks and the StyleGAN2 architecture. Our contribution is a novel method for inducing style transfer parameterized by a metric spac
Externí odkaz:
http://arxiv.org/abs/2208.04807
Autor:
Ruta, Dan, Gilbert, Andrew, Aggarwal, Pranav, Marri, Naveen, Kale, Ajinkya, Briggs, Jo, Speed, Chris, Jin, Hailin, Faieta, Baldo, Filipkowski, Alex, Lin, Zhe, Collomosse, John
We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a novel participatory method from experts studying at specialist art and de
Externí odkaz:
http://arxiv.org/abs/2203.05321
Autor:
Yuan, Xin, Lin, Zhe, Kuen, Jason, Zhang, Jianming, Wang, Yilin, Maire, Michael, Kale, Ajinkya, Faieta, Baldo
We develop an approach to learning visual representations that embraces multimodal data, driven by a combination of intra- and inter-modal similarity preservation objectives. Unlike existing visual pre-training methods, which solve a proxy prediction
Externí odkaz:
http://arxiv.org/abs/2104.12836
Autor:
Ruta, Dan, Motiian, Saeid, Faieta, Baldo, Lin, Zhe, Jin, Hailin, Filipkowski, Alex, Gilbert, Andrew, Collomosse, John
We present ALADIN (All Layer AdaIN); a novel architecture for searching images based on the similarity of their artistic style. Representation learning is critical to visual search, where distance in the learned search embedding reflects image simila
Externí odkaz:
http://arxiv.org/abs/2103.09776
Text-visual (or called semantic-visual) embedding is a central problem in vision-language research. It typically involves mapping of an image and a text description to a common feature space through a CNN image encoder and a RNN language encoder. In
Externí odkaz:
http://arxiv.org/abs/1905.13339
Autor:
Ruta, Dan, Gilbert, Andrew, Aggarwal, Pranav, Marri, Naveen, Kale, Ajinkya, Briggs, Jo, Speed, Chris, Jin, Hailin, Faieta, Baldo, Filipkowski, Alex, Lin, Zhe, Collomosse, John
Publikováno v:
Ruta, D, Gilbert, A, Aggarwal, P, Marri, N, Kale, A, Briggs, J, Speed, C, Jin, H, Faieta, B, Filipkowski, A, Lin, Z & Collomosse, J 2022, StyleBabel : Artistic style tagging and captioning . in S Avidan, G Brostow, M Cissé & G M Farinella (eds), Computer Vision – ECCV 2022 . Lecture Notes in Computer Science, pp. 219-236, European Conference on Computer Vision 2022, Tel Aviv, Israel, 23/10/22 . https://doi.org/10.1007/978-3-031-20074-8_13
We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a novel participatory method from experts studying at specialist art and de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3094::bac60c0d43d9441109053726719c6ede
https://www.pure.ed.ac.uk/ws/files/289807467/RutaEtal2022ECCVStyleBabelArtisticStyleTagging.pdf
https://www.pure.ed.ac.uk/ws/files/289807467/RutaEtal2022ECCVStyleBabelArtisticStyleTagging.pdf
Autor:
Ruta, Dan, Gilbert, Andrew, Aggarwal, Pranav, Kale, Ajinkya, Briggs, Jo, Speed, Chris, Jin, Halin, Faieta, Baldo, Filipkowski, Alex, Lin, Zhe, Collomosse, John
Publikováno v:
Computer Vision – ECCV 2022: 17th European Conference
We present StyleBabel, a unique open access dataset of natural language captions and free-form tags describing the artistic style of over 135K digital artworks, collected via a novel participatory method from experts studying at specialist art and de
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::bd8f0e112a3caa9f584dd9bbde7bdbb0
https://nrl.northumbria.ac.uk/id/eprint/49791/1/Dan_Ruta_StyleBabel_ECCV_3_.pdf
https://nrl.northumbria.ac.uk/id/eprint/49791/1/Dan_Ruta_StyleBabel_ECCV_3_.pdf