Shadow Detection
38 papers with code • 1 benchmarks • 3 datasets
SBU
SOBA
Latest papers
When SAM Meets Shadow Detection
As a promptable generic object segmentation model, segment anything model (SAM) has recently attracted significant attention, and also demonstrates its powerful performance.
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
tianrun-chen/sam-adapter-pytorch
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We can even outperform task-specific network models and achieve state-of-the-art performance in the task we tested: camouflaged object detection, shadow detection.
Explicit Visual Prompting for Low-Level Structure Segmentations
nifangbaage/explicit-visual-prompt
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CVPR 2023
Different from the previous visual prompting which is typically a dataset-level implicit embedding, our key insight is to enforce the tunable parameters focusing on the explicit visual content from each individual image, i. e., the features from frozen patch embeddings and the input's high-frequency components.
Adaptive Illumination Mapping for Shadow Detection in Raw Images
In this paper, we propose a novel method to detect shadows from raw images.
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Shadow removal improves the visual quality and legibility of digital copies of documents.
Instance Shadow Detection with A Single-Stage Detector
stevewongv/InstanceShadowDetection
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This paper formulates a new problem, instance shadow detection, which aims to detect shadow instance and the associated object instance that cast each shadow in the input image.
SpA-Former: Transformer image shadow detection and removal via spatial attention
zhangbaijin/spatial-transformer-shadow-removal
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In this paper, we propose an end-to-end SpA-Former to recover a shadow-free image from a single shaded image.
Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training
Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset.
Single-Stage Instance Shadow Detection with Bidirectional Relation Learning
Instance shadow detection aims to find shadow instances paired with the objects that cast the shadows.
Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry
esa/snerf
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To accommodate for changing light source conditions both from a directional light source (the Sun) and a diffuse light source (the sky), we extend the NeRF approach in two ways.
