Image Matting
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Benchmarks
Composition-1K
AM-2K
P3M-10k
AIM-500
Adobe Matting
Distinctions-646
AMD
PPM-100
Most implemented
ViTMatte: Boosting Image Matting with Pretrained Plain Vision Transformers
MODNet: Real-Time Trimap-Free Portrait Matting via Objective Decomposition
Deep Image Matting
Index Network
Towards Ghost-free Shadow Removal via Dual Hierarchical Aggregation Network and Shadow Matting GAN
Castle in the Sky: Dynamic Sky Replacement and Harmonization in Videos
Papers
Self-supervised Automatic Matting
High-quality alpha mattes are notoriously expensive to annotate, creating a fundamental data bottleneck for deep image matting. While prior work attempts to reduce annotation cost using coarser labels like trimaps or mas…
Image MattingSAM2Matting: Generalized Image and Video Matting
Despite impressive advances in image matting, video matting remains challenging due to the inherent gap between high-level tracking, which requires frame-wise understanding, and low-level matting, which focuses on extrem…
Domain GeneralizationImage MattingToward Real-World High-Precision Image Matting and Segmentation
High-precision scene parsing tasks, including image matting and dichotomous segmentation, aim to accurately predict masks with extremely fine details (such as hair). Most existing methods focus on salient, single foregro…
Domain AdaptationScene ParsingImage MattingSegment and Matte Anything in a Unified Model
Segment Anything (SAM) has recently pushed the boundaries of segmentation by demonstrating zero-shot generalization and flexible prompting after training on over one billion masks. Despite this, its mask prediction accur…
Zero-shot GeneralizationImage SegmentationImage MattingGuardians of the Hair: Rescuing Soft Boundaries in Depth, Stereo, and Novel Views
Soft boundaries, like thin hairs, are commonly observed in natural and computer-generated imagery, but they remain challenging for 3D vision due to the ambiguous mixing of foreground and background cues. This paper intro…
Monocular Depth EstimationNovel View SynthesisImage MattingMatAnyone 2: Scaling Video Matting via a Learned Quality Evaluator
Video matting remains limited by the scale and realism of existing datasets. While leveraging segmentation data can enhance semantic stability, the lack of effective boundary supervision often leads to segmentation-like …
Image Matting