Author Archives: Mohit Maithani
We have already seen a couple of pose estimation and face detection techniques in our previous article like 3ddfa-v2, OpenPose, Nvidia Imaginaire(Image & Video translation GAN Library), Yolov5, OneNet and many more. Today we will see a new face pose estimation, detection and alignment technique that uses 6DoF(degree of freedom) and 3D face estimation without…
The post img2pose: Guide to Face Alignment, Detection and Pose Estimation using 6DoF appeared first on Analytics India Magazine.
We have already seen a couple of pose estimation and face detection techniques in our previous article like 3ddfa-v2, OpenPose, Nvidia Imaginaire(Image & Video translation GAN Library), Yolov5, OneNet and many more. Today we will see a new face pose estimation, detection and alignment technique that uses 6DoF(degree of freedom) and 3D face estimation without…
The post img2pose: Guide to Face Alignment, Detection and Pose Estimation using 6DoF appeared first on Analytics India Magazine.
We have already seen a couple of pose estimation and face detection techniques in our previous article like 3ddfa-v2, OpenPose, Nvidia Imaginaire(Image & Video translation GAN Library), Yolov5, OneNet and many more. Today we will see a new face pose estimation, detection and alignment technique that uses 6DoF(degree of freedom) and 3D face estimation without…
The post img2pose: Guide to Face Alignment, Detection and Pose Estimation using 6DoF appeared first on Analytics India Magazine.
PoseCNN(Convolutional Neural Network) is an end to end framework for 6D object pose estimation, It calculates the 3D translation of the object by localizing the mid of the image and predicting its distance from the camera, and the rotation is calculated by relapsing to a quaternion representation. PoseCNN is papered by Yu Xiang, Tanner Schmidt,…
The post Guide To 6D Object Pose Estimation Using PoseCNN appeared first on Analytics India Magazine.
we have learned how self-supervised depth estimation (SDE) can be used to improve semantic segmentation, in both semis and fully supervised configuration.
The post Guide to Self-Supervised Depth Estimation for Semantic Segmentation appeared first on Analytics India Magazine.
We have seen enough of the optimizers previously in Tensorflow and PyTorch library, today we will be discussing a specific one i.e. AdaBelief. Almost every neural network and machine learning algorithm use optimizers to optimize their loss function using gradient descent. There are many optimizers available in PyTorch as well as TensorFlow for a specific…
The post Guide To The Latest AdaBelief Optimizer for Machine/Deep learning appeared first on Analytics India Magazine.
YolatEdge is one of the first competitive instanced segmentation techniques that can run on small devices with great real-time speed, It can reach up to 30fps on Nvidia Jetson AGX Xavier and 172fps on RTX 2080Ti. YolactEdge techniques come with Resnet-101 backbone which takes 550×550 resolution image as input. It paper called YolactEdge: Real-time Instance…
The post Introduction To YolactEdge For Real-time Object Segmentation On Edge Device appeared first on Analytics India Magazine.
Recently Salesforce Research launched an open-sourced framework for economic policy design and simulation: AI Economist. It is an economic simulation environment in which Artificial intelligence agents extract and trade resources, make houses, earn salaries, and pay taxes to the government bodies. It is a reinforcement learning(RL) problem to tax research to provide simulation and data-driven…
The post Salesforce Launches AI-Economist: A Complete Guide With Python Codes appeared first on Analytics India Magazine.
3D dense face alignment(3DDFA) is a trending technique for many face tasks, For example, object recognition, animation, tracking, image restoration, and many more. For now, most of the studies in 3DDFA are divided into two categories: 3D Morphable Model(3DMM) parameter regression, and Dense vertices regression. Now Existing method of 3D dense face alignment only focuses…
The post Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework appeared first on Analytics India Magazine.
3D dense face alignment(3DDFA) is a trending technique for many face tasks, For example, object recognition, animation, tracking, image restoration, and many more. For now, most of the studies in 3DDFA are divided into two categories: 3D Morphable Model(3DMM) parameter regression, and Dense vertices regression. Now Existing method of 3D dense face alignment only focuses…
The post Guide Towards Fast, Accurate, and Stable 3D Dense Face Alignment(3DDFA-V2) Framework appeared first on Analytics India Magazine.