Search Results for author:
Found 17 papers, 6 papers with code
RRR-Net: Reusing, Reducing, and Recycling a Deep Backbone Network
It has become mainstream in computer vision and other machine learning domains to reuse backbone networks pre-trained on large datasets as preprocessors.
Efficient Automation of Neural Network Design: A Survey on Differentiable Neural Architecture Search
In the past few years, Differentiable Neural Architecture Search (DNAS) rapidly imposed itself as the trending approach to automate the discovery of deep neural network architectures.
Kernel function impact on convolutional neural networks
This paper investigates the usage of kernel functions at the different layers in a convolutional neural network.
Alphazzle: Jigsaw Puzzle Solver with Deep Monte-Carlo Tree Search
Solving jigsaw puzzles requires to grasp the visual features of a sequence of patches and to explore efficiently a solution space that grows exponentially with the sequence length.
NASiam: Efficient Representation Learning using Neural Architecture Search for Siamese Networks
In this article, we present NASiam, a novel approach that uses for the first time differentiable NAS to improve the multilayer perceptron projector and predictor (encoder/predictor pair) architectures inside siamese-networks-based contrastive learning frameworks (e. g., SimCLR, SimSiam, and MoCo) while preserving the simplicity of previous baselines.
Learnable Triangulation for Deep Learning-based 3D Reconstruction of Objects of Arbitrary Topology from Single RGB Images
It is composed of of (1) a Vertex Generation Network (VGN), which predicts the initial 3D locations of the object's vertices from an input RGB image, (2) a differentiable triangulation layer, which learns in a non-supervised manner, using a novel reinforcement learning algorithm, the best triangulation of the object's vertices, and finally, (3) a hierarchical mesh refinement network that uses graph convolutions to refine the initial mesh.
D-DARTS: Distributed Differentiable Architecture Search
This approach is accompanied by a novel metric that measures the distance between architectures inside our custom search space.
Kernelized dense layers for facial expression recognition
Fully connected layer is an essential component of Convolutional Neural Networks (CNNs), which demonstrates its efficiency in computer vision tasks.
Facial Expression Recognition
Facial Expression Recognition (FER)
SSP-Net: Scalable Sequential Pyramid Networks for Real-Time 3D Human Pose Regression
In this paper we propose a highly scalable convolutional neural network, end-to-end trainable, for real-time 3D human pose regression from still RGB images.
Ranked #60 on
3D Human Pose Estimation
on MPI-INF-3DHP
Deepzzle: Solving Visual Jigsaw Puzzles with Deep Learning andShortest Path Optimization
We use a two-step method to obtain the reassemblies: 1) a neural network predicts the positions of the fragments despite the gaps between them; 2) a graph that leads to the best reassemblies is made from these predictions.
Multi-task Deep Learning for Real-Time 3D Human Pose Estimation and Action Recognition
In this work, we propose a multi-task framework for jointly estimating 2D or 3D human poses from monocular color images and classifying human actions from video sequences.
Ranked #142 on
3D Human Pose Estimation
on Human3.6M
Consensus-based Optimization for 3D Human Pose Estimation in Camera Coordinates
3D human pose estimation is frequently seen as the task of estimating 3D poses relative to the root body joint.
Ranked #69 on
3D Human Pose Estimation
on Human3.6M
Image Reassembly Combining Deep Learning and Shortest Path Problem
This paper addresses the problem of reassembling images from disjointed fragments.
Jigsaw Puzzle Solving Using Local Feature Co-Occurrences in Deep Neural Networks
Archaeologists are in dire need of automated object reconstruction methods.
2D/3D Pose Estimation and Action Recognition using Multitask Deep Learning
Action recognition and human pose estimation are closely related but both problems are generally handled as distinct tasks in the literature.
Ranked #1 on
Action Recognition In Videos
on NTU RGB+D
Human Pose Regression by Combining Indirect Part Detection and Contextual Information
In this paper, we propose an end-to-end trainable regression approach for human pose estimation from still images.
Ranked #11 on
Pose Estimation
on Leeds Sports Poses
Covariance Descriptors for 3D Shape Matching and Retrieval
We evaluate the performance of the proposed Bag of Covariance Matrices framework on 3D shape matching and retrieval applications and demonstrate its superiority compared to descriptor-based techniques.
