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Found 8 papers, 2 papers with code
Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking Approach
Detecting tiny objects in a high-resolution video is challenging because the visual information is little and unreliable.
Hybrid Loss for Learning Single-Image-based HDR Reconstruction
It makes the reconstruction faithful to the input.
Classification-Reconstruction Learning for Open-Set Recognition
Existing open-set classifiers rely on deep networks trained in a supervised manner on known classes in the training set; this causes specialization of learned representations to known classes and makes it hard to distinguish unknowns from knowns.
Cross-connected Networks for Multi-task Learning of Detection and Segmentation
We evaluated our proposed architecture on a combination of detection and segmentation using two datasets.
Differentiating Objects by Motion: Joint Detection and Tracking of Small Flying Objects
While generic object detection has achieved large improvements with rich feature hierarchies from deep nets, detecting small objects with poor visual cues remains challenging.
Continuous 3D Label Stereo Matching using Local Expansion Moves
The local expansion moves extend traditional expansion moves by two ways: localization and spatial propagation.
Superdifferential Cuts for Binary Energies
We then present our method as generalization of SSP, which is further shown to generalize several state-of-the-art techniques for higher-order and pairwise non-submodular functions [Ayed13, Gorelick14, Tang14].
Graph Cut based Continuous Stereo Matching using Locally Shared Labels
We present an accurate and efficient stereo matching method using locally shared labels, a new labeling scheme that enables spatial propagation in MRF inference using graph cuts.
