Devi Parikh, Songwei Ge, Vedanuj Goswami, C Zitnick, Tu-Berlin Bird, Quickdraw Bird
We lifted 12 functions out of this paper's own repositories and ran 10 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| facebookresearch/DoodlerGAN | canonical | 10 of 12 |
| Function | Status | Where it lives |
|---|---|---|
| Discriminator | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("3c595cc17d5b85ba") |
| DiscriminatorBlock | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("20a4f6204affb3ef") |
| EncoderBlock_unet | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("ed29dc3ccb2b5b3b") |
| Encoder_unet | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("36558825ea54044c") |
| Flatten | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("8818002d32451ab2") |
| GeneratorBlock | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("85aff785262093b0") |
| Generator_unet | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("3add9642c3b47498") |
| RGBBlock | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("ad92582b3ff8e62d") |
| StyleVectorizer | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("a1c88e05be5f5cae") |
| leaky_relu | Ran | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("870b0f7a0a7cfeb6") |
| Conv2DMod | Not yet run | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("0efd23bf3e72a0fa") |
| StyleGAN2_cond_unet | Not yet run | facebookresearch/DoodlerGAN/part_generator.py code served (permissive licence) · get_code("df6d3540e200d9f5") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Sketching or doodling is a popular creative activity that people engage in. However, most existing work in automatic sketch understanding or generation has focused on sketches that are quite mundane. In this work, we introduce two datasets of creative sketches -Creative Birds and Creative Creatures -containing 10k sketches each along with part annotations. We propose DoodlerGANa part-based Generative Adversarial Network (GAN) -to generate unseen compositions of novel part appearances. Quantitative evaluations as well as human studies demonstrate that sketches generated by our approach are more creative and of higher quality than existing approaches. In fact, in Creative Birds, subjects prefer sketches generated by DoodlerGAN over those drawn by humans! Our code, datasets and demo can be found at songweige.github.io/ projects/creative_sketech_generation/home.html.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2011.10039")
get_code_for_paper("2011.10039")
have("2011.10039")
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