Shadow Detection
38 papers with code • 1 benchmarks • 3 datasets
Most implemented papers
Triple-cooperative Video Shadow Detection
The bottleneck is the lack of a well-established dataset with high-quality annotations for video shadow detection.
Shadow Neural Radiance Fields for Multi-view Satellite Photogrammetry
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.
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.
Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training
Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset.
ShaDocNet: Learning Spatial-Aware Tokens in Transformer for Document Shadow Removal
Shadow removal improves the visual quality and legibility of digital copies of documents.
Adaptive Illumination Mapping for Shadow Detection in Raw Images
In this paper, we propose a novel method to detect shadows from raw images.
Explicit Visual Prompting for Low-Level Structure Segmentations
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.
SAM Fails to Segment Anything? -- SAM-Adapter: Adapting SAM in Underperformed Scenes: Camouflage, Shadow, Medical Image Segmentation, and More
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.
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.
Detect Any Shadow: Segment Anything for Video Shadow Detection
Segment anything model (SAM) has achieved great success in the field of natural image segmentation.