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OpenPose-style keypoint skeleton for the figure: a pose-control input for guided generation and a target for pose-estimation checks.
Sparse scribble derived from the edges: the loose hand-drawn control input for scribble-guided image generation.
Semantic segmentation map (subject vs background): the label reference for segmentation-conditioned generation and mask-quality scoring.
Binary Canny edge map extracted from the ground truth. Feed as a structure-control input and score the generated result against the reference.
Synthetic depth map (near = bright) for depth-conditioned generation and monocular depth-estimation regression against a known reference.
Clean line-art extraction (black lines on white) for line-art-conditioned generation and line-extraction quality tests.
Tangent-space surface-normal map encoded from the scene depth: a normal-conditioning input for guided generation and relighting tests.
Sparse scribble derived from the edges: the loose hand-drawn control input for scribble-guided image generation.
Semantic segmentation map (subject vs background): the label reference for segmentation-conditioned generation and mask-quality scoring.
Binary Canny edge map extracted from the ground truth. Feed as a structure-control input and score the generated result against the reference.
Synthetic depth map (near = bright) for depth-conditioned generation and monocular depth-estimation regression against a known reference.
Clean line-art extraction (black lines on white) for line-art-conditioned generation and line-extraction quality tests.
Tangent-space surface-normal map encoded from the scene depth: a normal-conditioning input for guided generation and relighting tests.
Sparse scribble derived from the edges: the loose hand-drawn control input for scribble-guided image generation.
Semantic segmentation map (subject vs background): the label reference for segmentation-conditioned generation and mask-quality scoring.
Binary Canny edge map extracted from the ground truth. Feed as a structure-control input and score the generated result against the reference.
Synthetic depth map (near = bright) for depth-conditioned generation and monocular depth-estimation regression against a known reference.
Clean line-art extraction (black lines on white) for line-art-conditioned generation and line-extraction quality tests.
Tangent-space surface-normal map encoded from the scene depth: a normal-conditioning input for guided generation and relighting tests.
Sparse scribble derived from the edges: the loose hand-drawn control input for scribble-guided image generation.
Semantic segmentation map (subject vs background): the label reference for segmentation-conditioned generation and mask-quality scoring.
Binary Canny edge map extracted from the ground truth. Feed as a structure-control input and score the generated result against the reference.
Synthetic depth map (near = bright) for depth-conditioned generation and monocular depth-estimation regression against a known reference.
Clean line-art extraction (black lines on white) for line-art-conditioned generation and line-extraction quality tests.
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