MangaNinja: Line Art Colorization with Precise Reference Following
Derived from diffusion models, MangaNinjia specializes in the task of
reference-guided line art colorization. We incorporate two thoughtful designs
to ensure precise character detail transcription, including a patch shuffling
module to facilitate correspondence learning between the reference color image
and the target line art, and a point-driven control scheme to enable
fine-grained color matching. Experiments on a self-collected benchmark
demonstrate the superiority of our model over current solutions in terms of
precise colorization. We further showcase the potential of the proposed
interactive point control in handling challenging cases, cross-character
colorization, multi-reference harmonization, beyond the reach of existing
algorithms.
678727aadd2e5dbecdf08fe3
Zhiheng Liu
admin_assigned
2025-01-15T16:42:29.526Z
6479925ab77e18dbf640bd67
/avatars/bb52ecd22ca4b49157f8668be35409e7.svg
Zhiheng Liu
user
Johanan0528
678727aadd2e5dbecdf08fe4
Ka Leong Cheng
admin_assigned
2025-01-15T16:42:34.938Z
64acd2ec39fcfebff8c79c00
/avatars/9419384846b92182f2c47ce2fbd0f8d3.svg
Ka Leong Cheng
user
felixcheng97
678727aadd2e5dbecdf08fe5
Xi Chen
admin_assigned
2025-01-15T16:42:44.702Z
644a1b6401e18bf93a6f45c1
https://cdn-avatars.huggingface.co/v1/production/uploads/644a1b6401e18bf93a6f45c1/P0i_CgCrIzOS2tYRlxoE9.png
xichen
user
xichenhku
678727aadd2e5dbecdf08fe6
Jie Xiao
admin_assigned
2025-01-15T16:43:12.886Z
646b2767ec9a61e8717a41a7
/avatars/5503aefdfd6cddd6f83bf9fbcced4c90.svg
jiexiao
user
jiexiao
678727aadd2e5dbecdf08fe7
Hao Ouyang
678727aadd2e5dbecdf08fe8
Kai Zhu
678727aadd2e5dbecdf08fe9
Yu Liu
678727aadd2e5dbecdf08fea
Yujun Shen
678727aadd2e5dbecdf08feb
Qifeng Chen
admin_assigned
2025-01-15T16:43:50.764Z
6467b121e7a6a374fd19b44b
/avatars/3f2874d58986d651aef55e3408b05700.svg
Qifeng Chen
user
cqf
678727aadd2e5dbecdf08fec
Ping Luo
MangaNinja: Line Art Colorization with Precise Reference Following
Derived from diffusion models, MangaNinjia specializes in the task of
reference-guided line art colorization. We incorporate two thoughtful designs
to ensure precise character detail transcription, including a patch shuffling
module to facilitate correspondence learning between the reference color image
and the target line art, and a point-driven control scheme to enable
fine-grained color matching. Experiments on a self-collected benchmark
demonstrate the superiority of our model over current solutions in terms of
precise colorization. We further showcase the potential of the proposed
interactive point control in handling challenging cases, cross-character
colorization, multi-reference harmonization, beyond the reach of existing
algorithms.
MangaNinjia, a diffusion model-based approach, enhances line art colorization with patch shuffling and point-driven control for precise detail and color matching.
diffusion models MangaNinjia reference-guided line art colorization patch shuffling module correspondence learning point-driven control scheme fine-grained color matching cross-character colorization multi-reference harmonization