Test sets: • LA30/Cas-Gnn. SALIENT OBJECT DETECTION Ranked #4 on • qduOliver/MQP Ranked #3 on • JingZhang617/UCNet Coco: val 2017; Pascal VOC: test 2007; Cityscapes: val; ( Image credit: Benchmarking Robustness in Object Detection ), CVPR 2018 Current works either simply distill prior knowledge from the corresponding depth map for handling the RGB-image or blindly fuse color and geometric information to generate the coarse depth-aware representations, hindering the performance of RGB-D saliency detectors. The recently-concluded CVPR 2020 had quite a large number of contributions in pushing object detection forward. Object Detection with Deep Learning: A Review Zhong-Qiu Zhao, Member, IEEE, Peng Zheng, Shou-tao Xu, and Xindong Wu, Fellow, IEEE Abstract—Due to object detection’s close relationship with video analysis and image understanding, it has attracted much research attention in recent years. Every object has its own class such as all circles are round, which are used while recognizing the objects. Ranked #1 on Browse our catalogue of tasks and access state-of-the-art solutions. ROBUST OBJECT DETECTION Inspired by the observation that RGB and depth modalities actually present certain commonality in distinguishing salient objects, a novel joint learning and densely cooperative fusion (JL-DCF) architecture is designed to learn from both RGB and depth inputs through a shared network backbone, known as the Siamese architecture. Benchmarking Robustness in Object Detection, Benchmarking Robustness in Object Detection: Autonomous Driving when Winter is Coming, Domain Adaptive Faster R-CNN for Object Detection in the Wild, Image-to-Image Translation Title: Rich feature hierarchies for accurate object detection and semantic segmentation DATA AUGMENTATION Get the latest machine learning methods with code. RGB SALIENT OBJECT DETECTION There are so many, in fact, that compiling any comprehensive review of the state of the art is beyond the scope of any reasonable length paper. Browse our catalogue of tasks and access state-of-the-art solutions. RGB-D Salient Object Detection Browse our catalogue of tasks and access state-of-the-art solutions. Though remarkable progress has been achieved, we observe that the closer the pixel is to the edge, the more difficult it is to be predicted, because edge pixels have a very imbalance distribution. Clustered Object Detection in Aerial Images Fan Yang1 Heng Fan1 Peng Chu1 Erik Blasch2 Haibin Ling3,1∗ 1Department of Computer and Information Sciences, Temple University, Philadelphia, USA 2Air Force Research Lab, USA 3Department Computer Science, Stony Brook University, Stony Brook, NY, USA. •. R-FCN: Object Detection via Region-based Fully Convolutional Networks. on SIP, Label Decoupling Framework for Salient Object Detection, Progressively Guided Alternate Refinement Network for RGB-D Salient Object Detection, Cascade Graph Neural Networks for RGB-D Salient Object Detection, RGB-D Salient Object Detection •. Video object detection is the task of detecting objects from a video as opposed to images. BIRANet yields 72. VIDEO SALIENT OBJECT DETECTION, 7 Aug 2020 Let’s move forward with our Object Detection Tutorial and understand it’s various applications in the industry. •. •. ROBUST OBJECT DETECTION, ICCV 2019 ICCV 2019 • VITA-Group/UAV-NDFT • Object detection from images captured by Unmanned Aerial Vehicles (UAVs) is becoming increasingly useful. To adapt to the domain shift, the model is trained on the target domain using a set of noisy object bounding boxes that are obtained by a detection model trained only in the source domain. 17 Apr 2020 • bethgelab/imagecorruptions. A robust object detection is crucial for reliable results, hence the state-of-the-art deep neural network Mask-RCNN is applied for that purpose. Object Detection from Scratch with Deep Supervision Abstract: In this paper, we propose Deeply Supervised Object Detectors (DSOD), an object detection framework that can be trained from scratch. Get the latest machine learning methods with code. The results demonstrate the effectiveness of our proposed approach for robust object detection in various domain shift scenarios. on SIP VIDEO SALIENCY DETECTION 2, the high intrinsic similarities between the target objectand thebackgroundmakeCODfarmore challenging than the traditional salient object detection [1,5,17,25,62– 66,68] or generic object detection [4,79]. Their performance easily stagnates by constructing complex ensembles which combine multiple low-level image features with high-level context from object detectors and scene classifiers. RGB-D SALIENT OBJECT DETECTION Image-to-Image Translation Ranked #1 on Below you can find a continuously updating list of object detection models. on HKU-IS, RGB SALIENT OBJECT DETECTION 3% average AP/AR on the NuScenes dataset, which is better than the performance of our base network Faster-RCNN with Feature pyramid network(FFPN). TRAFFIC CLASSIFICATION, 31 Aug 2020 II. • wuzhenyubuaa/TSNet Robust Object Detection • ShuhanChen/PGAR_ECCV20 on Cityscapes-to-Foggy Cityscapes, Robust Object Detection •. SALIENCY PREDICTION, 28 Aug 2020 ICCV 2019 8 min read. VIDEO SALIENT OBJECT DETECTION. Deep architectures for object detection and parsing have been motivated by part-based models and traditionally are called compositional models, where the object is expressed as layered composition of image primitives. 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