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On the Importance of Large Objects in CNN Based Object Detection Algorithms
In this paper, we highlight the importance of large objects in learning features that are critical for all sizes.
Improving Pixel-Level Contrastive Learning by Leveraging Exogenous Depth Information
In this paper we will focus on the depth information, which can be obtained by using a depth estimation network or measured from available data (stereovision, parallax motion, LiDAR, etc.).
Where is the Fake? Patch-Wise Supervised GANs for Texture Inpainting
We tackle the problem of texture inpainting where the input images are textures with missing values along with masks that indicate the zones that should be generated.
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