Papers Mirror Detection
“Mirror Detection” 태그가 달린 논문 14편 · 필터 해제
Detect Any Mirrors: Boosting Learning Reliability on Large-Scale Unlabeled Data with an Iterative Data Engine
Mirror detection is a challenging task because a mirror's visual appearance varies depending on the reflected content. Due to limited annotated data, current methods failed to generalize well for detecting diverse mi…
Mirror DetectionPseudo LabelWhen SAM2 Meets Video Shadow and Mirror Detection
As the successor to the Segment Anything Model (SAM), the Segment Anything Model 2 (SAM2) not only improves performance in image segmentation but also extends its capabilities to video segmentation. However, its effectiv…
Image SegmentationMirror DetectionSegmentationSemantic Segmentation+4SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
Image segmentation plays an important role in vision understanding. Recently, the emerging vision foundation models continuously achieved superior performance on various tasks. Following such success, in this paper, we p…
Image SegmentationMarine Animal SegmentationMedical Image SegmentationMirror Detection+4Fusion of Short-term and Long-term Attention for Video Mirror Detection
Techniques for detecting mirrors from static images have witnessed rapid growth in recent years. However, these methods detect mirrors from single input images. Detecting mirrors from video requires further consideration…
Mirror Detection3DRef: 3D Dataset and Benchmark for Reflection Detection in RGB and Lidar Data
Reflective surfaces present a persistent challenge for reliable 3D mapping and perception in robotics and autonomous systems. However, existing reflection datasets and benchmarks remain limited to sparse 2D data. This pa…
Image SegmentationMirror DetectionPoint Cloud SegmentationSegmentation+1Effective Video Mirror Detection with Inconsistent Motion Cues
Image-based mirror detection has recently undergone rapid research due to its significance in applications such as robotic navigation semantic segmentation and scene reconstruction. Recently VMD-Net was proposed as t…
Edge DetectionMirror DetectionOptical Flow EstimationSemantic SegmentationLearning To Detect Mirrors From Videos via Dual Correspondences
Detecting mirrors from static images has received significant research interest recently. However, detecting mirrors over dynamic scenes is still under-explored due to the lack of a high-quality dataset and an effect…
Mirror DetectionSelf-supervised Pre-training for Mirror Detection
Existing mirror detection methods require supervised ImageNet pre-training to obtain good general-purpose image features. However, supervised ImageNet pre-training focuses on category-level discrimination and may not…
image-classificationImage ClassificationMirror DetectionSelf-Supervised LearningEfficient Mirror Detection via Multi-level Heterogeneous Learning
We present HetNet (Multi-level \textbf{Het}erogeneous \textbf{Net}work), a highly efficient mirror detection network. Current mirror detection methods focus more on performance than efficiency, limiting the real-time app…
Image SegmentationMirror DetectionSymmetry-Aware Transformer-based Mirror Detection
Mirror detection aims to identify the mirror regions in the given input image. Existing works mainly focus on integrating the semantic features and structural features to mine specific relations between mirror and non-mi…
DecoderMirror DetectionMirror-Yolo: A Novel Attention Focus, Instance Segmentation and Mirror Detection Model
Mirrors can degrade the performance of computer vision models, but research into detecting them is in the preliminary phase. YOLOv4 achieves phenomenal results in terms of object detection accuracy and speed, but it stil…
Instance SegmentationMirror Detectionobject-detectionObject Detection+1Learning Semantic Associations for Mirror Detection
Mirrors generally lack a consistent visual appearance, making mirror detection very challenging. Although recent works that are based on exploiting contextual contrasts and corresponding relations have achieved good …
Image SegmentationMirror DetectionFakeMix Augmentation Improves Transparent Object Detection
Detecting transparent objects in natural scenes is challenging due to the low contrast in texture, brightness and colors. Recent deep-learning-based works reveal that it is effective to leverage boundaries for transparen…
Data AugmentationMirror DetectionObjectobject-detection+3Progressive Mirror Detection
The mirror detection problem is important as mirrors can affect the performances of many vision tasks. It is a difficult problem as it requires an understanding of global scene semantics. Recently, a method was proposed …
DiversityEdge DetectionImage SegmentationMirror Detection