Awesome-Object-Shadow-Generation

Shadow generation resources

A curated collection of resources and papers on generating realistic 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

[pdf] Ziqi Yu, Jing Zhou, Zhongyun Bao, Gang Fu, Weilei He, Chao Liang, Chunxia Xiao: " " ACM MM (2024)
[pdf] Jing Zhou, Ziqi Yu, Zhongyun Bao, Gang Fu, Weilei He, Chao Liang, Chunxia Xiao: " " ACM MM (2024)
[pdf] Daniel Winter, Matan Cohen, Shlomi Fruchter, Yael Pritch, Alex Rav-Acha, Yedid Hoshen: " " ECCV (2024)
[pdf] Gemma Canet Tarrés, Zhe Lin, Zhifei Zhang, Jianming Zhang, Yizhi Song, Dan Ruta, Andrew Gilbert, John Collomosse, Soo Ye Kim:" " ECCV (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 1,196 about 2 months ago

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