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Found 10 papers, 3 papers with code
Learning To Detect Mirrors From Videos via Dual Correspondences
However, detecting mirrors over dynamic scenes is still under-explored due to the lack of a high-quality dataset and an effective method for video mirror detection (VMD).
Self-supervised Pre-training for Mirror Detection
Existing mirror detection methods require supervised ImageNet pre-training to obtain good general-purpose image features.
Efficient Mirror Detection via Multi-level Heterogeneous Learning
We present HetNet (Multi-level \textbf{Het}erogeneous \textbf{Net}work), a highly efficient mirror detection network.
Weakly-Supervised Camouflaged Object Detection with Scribble Annotations
To achieve this, we first relabel 4, 040 images in existing camouflaged object datasets with scribbles, which takes ~10s to label one image.
Symmetry-Aware Transformer-based Mirror Detection
Mirror detection aims to identify the mirror regions in the given input image.
Depth-aware Glass Surface Detection with Cross-modal Context Mining
This however poses substantial challenges on the operations of autonomous systems such as robots, self-driving cars and drones, as the glass panels can become transparent obstacles to the navigation. Existing works attempt to exploit various cues, including glass boundary context or reflections, as a prior.
Learning Semantic Associations for Mirror Detection
Inspired by this observation, we propose a model to exploit the semantic associations between the mirror and its surrounding objects for a reliable mirror localization.
Rich Context Aggregation With Reflection Prior for Glass Surface Detection
However, as it is only based on a general context integration operation and does not consider any specific glass surface properties, it gets confused when the images contain objects that are similar to glass surfaces and degenerates in challenging scenes with insufficient contexts.
Progressive Mirror Detection
Hence, we propose a model in this paper to progressively learn the content similarity between the inside and outside of the mirror while explicitly detecting the mirror edges.
