Awesome-Object-Shadow-Generation
Shadow generator resources
A curated collection of papers, code, and resources on generating plausible shadows for composite images.
A curated list of papers, code, and resources pertaining to object shadow generation.
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image-compositionshadow-generation
Awesome Object Shadow Generation / Papers | |||
| [arXiv] | Daniel Winter, Matan Cohen, Shlomi Fruchter, Yael Pritch, Alex Rav-Acha, Yedid Hoshen: " " arXiv preprint arXiv:2403.18818 (2024) | ||
| [arXiv] | Qingyang Liu, Junqi You, Jianting Wang, Xinhao Tao, Bo Zhang, Li Niu: " " CVPR (2024) | ||
| [arXiv] | Xinhao Tao, Junyan Cao, Yan Hong, Li Niu: " " AAAI (2024) | ||
| [paper] | Lucas Valença, Jinsong Zhang, Michaël Gharbi, Yannick Hold-Geoffroy, Jean-François Lalonde: " " SIGGRAPH Asia (2023) | ||
| [paper] | Quanling Meng, Shengping Zhang, Zonglin Li, Chenyang Wang, Weigang Zhang, Qingming Huang: " " T-MM (2023) | ||
| [paper] | Yichen Sheng, Jianming Zhang, Julien Philip, Yannick Hold-Geoffroy, Xin Sun, He Zhang, Lu Ling, Bedrich Benes: " " CVPR (2023) | ||
| [pdf] | Tianyanshi Liu, Yuhang Li, Youdong Ding: " " EITCE (2022) | ||
| [arXiv] | Yan Hong, Li Niu, Jianfu Zhang: " " AAAI (2022) | ||
| [arXiv] | Yichen Sheng, Yifan Liu, Jianming Zhang, Wei Yin, Oztireli Cengiz, He Zhang, Lin Zhe, Shechtman Eli, Bedrich Benes: " " ECCV (2022) | ||
| [pdf] | Yichen Sheng, Jianming Zhang, Bedrich Benes: " " CVPR (2021) oral | ||
| [pdf] | Daquan Liu, Chengjiang Long, Hongpan Zhang, Hanning Yu, Xinzhi Dong, Chunxia Xiao: " " CVPR (2020) | ||
| [pdf] | Shuyang Zhang, Runze Liang, Miao Wang: " " Computational Visual Media (2019) | ||
| [pdf] | Fangneng Zhan, Shijian Lu, Changgong Zhang, Feiying Ma, Xuansong Xie: " " ACCV (2020) | ||
Awesome Object Shadow Generation / Datasets | |||
| [pdf] | : It contains 3,000 quintuples, Each quintuple consists of 5 images 640×480 resolution: a synthetic image without the virtual object shadow and its corresponding image containing the virtual object shadow, a mask of the virtual object, a labeled real-world shadow matting and its corresponding labeled occluder | ||
| [pdf] | : It contains 840 training images with totally 2,999 object-shadow pairs and 160 test images with totally 624 object-shadow pairs | ||
| [pdf] | : It is a real-world shadow generation dataset constructed using object-shadow detection and inpainting models. It has 21, 575 images with 28, 573 valid object-shadow pairs | ||
| [pdf] | : It is a large-scale Rendered Shadow Generation dataset with 30 3D scenes, 788 3D foreground objects, and 280,000 object-shadow pairs | ||
Awesome Object Shadow Generation / Other Resources | |||
| Awesome-Image-Composition | 1,182 | 14 days ago | |