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Found 26 papers, 4 papers with code
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 #3 on
3D Face Reconstruction
on Florence
(RMSE Cooperative metric)
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.
Maintaining Reasoning Consistency in Compositional Visual Question Answering
Existing VQA models can answer a compositional question well, but cannot work well in terms of reasoning consistency in answering the compositional question and its sub-questions.
Exploring the Effect of Primitives for Compositional Generalization in Vision-and-Language
Compositional generalization is critical to simulate the compositional capability of humans, and has received much attention in the vision-and-language (V&L) community.
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.
Ranked #6 on
Point Cloud Registration
on FP-O-H
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.
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.
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.
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.
Video Captioning Using Weak Annotation
Through traversing the dependency trees, the sentences are generated to train the captioning model.
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.
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.
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.
Global-Aware Registration of Less-Overlap RGB-D Scans
We propose a novel method of registering less-overlap RGB-D scans.
Exploring Data Geometry for Continual Learning
Our method dynamically expands the geometry of the underlying space to match growing geometric structures induced by new data, and prevents forgetting by keeping geometric structures of old data into account.
Fast-StrucTexT: An Efficient Hourglass Transformer with Modality-guided Dynamic Token Merge for Document Understanding
Transformers achieve promising performance in document understanding because of their high effectiveness and still suffer from quadratic computational complexity dependency on the sequence length.
Neural 3D Scene Reconstruction from Multiple 2D Images without 3D Supervision
We improve the reconstruction quality of complex geometry scene regions with sparse depth obtained by using the geometric constraints.
Sparse Point Guided 3D Lane Detection
The high-resolution local information brought by sparse points refines 3D lanes in the BEV space hierarchically from low resolution to high resolution.
Video Anomaly Detection via Sequentially Learning Multiple Pretext Tasks
In this way, our method is able to reduce the difficulties of learning and avoid converging to sub-optimal solutions.
Parameterized Cost Volume for Stereo Matching
In this paper, we propose a parameterized cost volume to encode the entire disparity space using multi-Gaussian distribution.
Fine-Grained Annotation for Face Anti-Spoofing
In this paper, we propose a fine-grained annotation method for face anti-spoofing.
