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Found 3 papers, 1 papers with code
Deep Texture-Aware Features for Camouflaged Object Detection
Camouflaged object detection is a challenging task that aims to identify objects having similar texture to the surroundings.
Deep Multi-Model Fusion for Single-Image Dehazing
This paper presents a deep multi-model fusion network to attentively integrate multiple models to separate layers and boost the performance in single-image dehazing.
Bidirectional Feature Pyramid Network with Recurrent Attention Residual Modules for Shadow Detection
Second, we develop a bidirectional feature pyramid network (BFPN) to aggregate shadow contexts spanned across different CNN layers by deploying two series of RAR modules in the network to iteratively combine and refine context features: one series to refine context features from deep to shallow layers, and another series from shallow to deep layers.
Ranked #3 on
Shadow Detection
on SBU
