Ashish Patel 🇮🇳’s Post

𝗗𝗮𝘆-𝟭𝟴𝟬 Computer Vision Learning Progressively Guided Alternate Refinement Network for RGB-D 𝗦𝗮𝗹𝗶𝗲𝗻𝘁 𝗢𝗯𝗷𝗲𝗰𝘁 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻 by Northeastern University, Boston, USA Follow me for a similar post:  🇮🇳 Ashish Patel Interesting Facts : 🔸 This is a paper in ECCV2020 with over 15 citation. ------------------------------------------------------------------- 𝗔𝗺𝗮𝘇𝗶𝗻𝗴 𝗥𝗲𝘀𝗲𝗮𝗿𝗰𝗵 : https://lnkd.in/ekSFBNw Code : https://lnkd.in/edP8u5u ------------------------------------------------------------------- 𝗜𝗠𝗣𝗢𝗥𝗧𝗔𝗡𝗖𝗘 🔸 Aim to develop an efficient and compact deep network for RGB-D salient object detection, where the depth image provides complementary information to boost performance in complex scenarios. 🔸 Starting from a coarse initial prediction by a multi-scale residual block, It proposes a progressively guided alternate refinement network to refine it. 🔸 Instead of using ImageNet pre-trained backbone network, first construct a lightweight depth stream by learning from scratch, which can extract complementary features more efficiently with less redundancy. 🔸 Then, different from the existing fusion based methods, RGB and depth features are fed into proposed guided residual (GR) blocks alternately to reduce their mutual degradation.By assigning progressive guidance in the stacked GR blocks within each side-output, the false detection and missing parts can be well remedied. #computervision #artificialintelligence #data