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Found 16 papers, 1 papers with code
A Decomposition Model for Stereo Matching
In this paper, we present a decomposition model for stereo matching to solve the problem of excessive growth in computational cost (time and memory cost) as the resolution increases.
A Hyperbolic-to-Hyperbolic Graph Convolutional Network
Specifically, we developed a manifold-preserving graph convolution that consists of a hyperbolic feature transformation and a hyperbolic neighborhood aggregation.
Curvature Generation in Curved Spaces for Few-Shot Learning
Few-shot learning describes the challenging problem of recognizing samples from unseen classes given very few labeled examples.
Video Captioning Using Weak Annotation
Through traversing the dependency trees, the sentences are generated to train the captioning model.
Content-Aware Inter-Scale Cost Aggregation for Stereo Matching
In this paper, we present a content-aware inter-scale cost aggregation method that adaptively aggregates and upsamples the cost volume from coarse-scale to fine-scale by learning dynamic filter weights according to the content of the left and right views on the two scales.
Deep 3D Portrait from a Single Image
We evaluate the accuracy of our method both in 3D and with pose manipulation tasks on 2D images.
Relational Reasoning using Prior Knowledge for Visual Captioning
Extensive experiments on the MS-COCO image captioning benchmark and the MSVD video captioning benchmark validate the superiority of our method on leveraging prior commonsense knowledge to enhance relational reasoning for visual captioning.
Accurate 3D Face Reconstruction with Weakly-Supervised Learning: From Single Image to Image Set
Recently, deep learning based 3D face reconstruction methods have shown promising results in both quality and efficiency. However, training deep neural networks typically requires a large volume of data, whereas face images with ground-truth 3D face shapes are scarce.
Ranked #2 on
3D Face Reconstruction
on NoW Benchmark
Stitching Videos from a Fisheye Lens Camera and a Wide-Angle Lens Camera for Telepresence Robots
In this paper, we propose to stitch videos from the FF-camera with a wide-angle lens and the DF-camera with a fisheye lens for telepresence robots.
Deep Stereo Matching with Explicit Cost Aggregation Sub-Architecture
The cost aggregation sub-architecture is realized by a two-stream network: one for the generation of cost aggregation proposals, the other for the selection of the proposals.
Learning a Robust Representation via a Deep Network on Symmetric Positive Definite Manifolds
To this end, several new layers are introduced in our network, including a nonlinear kernel aggregation layer, an SPD matrix transformation layer, and a vectorization layer.
Anisotropic Diffusion-based Kernel Matrix Model for Face Liveness Detection
We use the anisotropic diffusion to enhance the edges and boundary locations of a face image, and the kernel matrix model to extract face image features which we call the diffusion-kernel (D-K) features.
A Hybrid Data Association Framework for Robust Online Multi-Object Tracking
In this paper, we present a hybrid data association framework with a min-cost multi-commodity network flow for robust online multi-object tracking.
Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration
The evaluation demonstrates that the proposed method is able to produce reliable registration results regardless of the initialization.
Temporal Dynamic Appearance Modeling for Online Multi-Person Tracking
The temporal dynamic makes a sufficient complement to the spatial structure of varying appearances in the feature space, which significantly improves the affinity measurement between trajectories and detections.
Discriminatively Trained And-Or Tree Models for Object Detection
This paper presents a method of learning reconfigurable And-Or Tree (AOT) models discriminatively from weakly annotated data for object detection.
