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Found 9 papers, 2 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).
Learning Image Harmonization in the Linear Color Space
In this paper, we propose a novel neural approach to harmonize the image colors in a camera-independent color space, in which color values are proportional to the scene radiance.
Self-supervised Pre-training for Mirror Detection
Existing mirror detection methods require supervised ImageNet pre-training to obtain good general-purpose image features.
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.
Learning Object Context for Novel-View Scene Layout Generation
We also show that our model enables a wide range of applications, including novel-view image synthesis, novel-view image editing, and amodal object estimation.
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.
Light Source Guided Single-Image Flare Removal From Unpaired Data
In particular, we first detect the light source regions and the flare regions separately, and then remove the flare artifacts based on the light source aware guidance.
Mitigating Intensity Bias in Shadow Detection via Feature Decomposition and Reweighting
These two phenomenons reveal that deep shadow detectors heavily depend on the intensity cue, which we refer to as intensity bias.
Scene Context-Aware Salient Object Detection
To our knowledge, such high-level semantic contextual information of image scenes is under-explored for saliency detection in the literature.
