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Found 23 papers, 10 papers with code
Joint 3D Layout and Depth Prediction from a Single Indoor Panorama Image
Leveraging the layout depth map as an intermediate representation, our proposed method outperforms existing methods for both panorama layout prediction and depth estimation.
Relational Prior Knowledge Graphs for Detection and Instance Segmentation
Humans have a remarkable ability to perceive and reason about the world around them by understanding the relationships between objects.
Intrinsic Image Decomposition Using Point Cloud Representation
The purpose of intrinsic decomposition is to separate an image into its albedo (reflective properties) and shading components (illumination properties).
Geometry-guided Feature Learning and Fusion for Indoor Scene Reconstruction
First, geometry-guided feature learning encodes geometric priors to contain view-dependent information.
SIGNet: Intrinsic Image Decomposition by a Semantic and Invariant Gradient Driven Network for Indoor Scenes
An ablation study is conducted showing that the use of the proposed priors and progressive CNN increase the IID performance.
Multi-person 3D pose estimation from a single image captured by a fisheye camera
Multi-person 3D pose estimation with absolute depths for a fisheye camera is a challenging task but with valuable applications in daily life, especially for video surveillance.
PIE-Net: Photometric Invariant Edge Guided Network for Intrinsic Image Decomposition
An extensive ablation study and large scale experiments are conducted showing that it is beneficial for edge-driven hybrid IID networks to make use of illumination invariant descriptors and that separating global and local cues helps in improving the performance of the network.
Generative Models for Multi-Illumination Color Constancy
However, most of the existing color constancy methods are designed for single light sources.
EDEN: Multimodal Synthetic Dataset of Enclosed GarDEN Scenes
Multimodal large-scale datasets for outdoor scenes are mostly designed for urban driving problems.
Spatio-temporal Features for Generalized Detection of Deepfake Videos
In this paper, we empirically show that existing approaches on image and sequence classifiers generalize poorly to new manipulation techniques.
Physics-based Shading Reconstruction for Intrinsic Image Decomposition
We investigate the use of photometric invariance and deep learning to compute intrinsic images (albedo and shading).
Multi-Loss Weighting with Coefficient of Variations
In this paper, we propose a weighting scheme based on the coefficient of variations and set the weights based on properties observed while training the model.
Kinship Identification through Joint Learning Using Kinship Verification Ensembles
The experiments further show significant performance improvement of kinship verification when trained on the same dataset with more realistic distributions.
ShadingNet: Image Intrinsics by Fine-Grained Shading Decomposition
The aim is to distinguish strong photometric effects from reflectance variations.
On the Benefit of Adversarial Training for Monocular Depth Estimation
For the quality of the image reconstruction and disparity prediction, a combination of different losses is used, including L1 image reconstruction losses and left-right disparity smoothness.
Deception Detection by 2D-to-3D Face Reconstruction from Videos
Lies and deception are common phenomena in society, both in our private and professional lives.
Improving Face Detection Performance with 3D-Rendered Synthetic Data
In this paper, we provide a synthetic data generator methodology with fully controlled, multifaceted variations based on a new 3D face dataset (3DU-Face).
Color Constancy by GANs: An Experimental Survey
In this paper, we formulate the color constancy task as an image-to-image translation problem using GANs.
Automatic Generation of Dense Non-rigid Optical Flow
There hardly exists any large-scale datasets with dense optical flow of non-rigid motion from real-world imagery as of today.
Inferring Point Clouds from Single Monocular Images by Depth Intermediation
In this paper, we propose a pipeline to generate 3D point cloud of an object from a single-view RGB image.
Joint Learning of Intrinsic Images and Semantic Segmentation
To that end, we propose a supervised end-to-end CNN architecture to jointly learn intrinsic image decomposition and semantic segmentation.
Object Class Detection and Classification using Multi Scale Gradient and Corner Point based Shape Descriptors
This paper presents a novel multi scale gradient and a corner point based shape descriptors.
Detect2Rank : Combining Object Detectors Using Learning to Rank
Experiments on the PASCAL VOC07 and VOC10 datasets show that the proposed method significantly outperforms single object detectors, DPM (8. 4%), CN (6. 8%) and EES (17. 0%) on VOC07 and DPM (6. 5%), CN (5. 5%) and EES (16. 2%) on VOC10.
