Search Results for author:
Found 32 papers, 9 papers with code
Particularity beyond Commonality: Unpaired Identity Transfer with Multiple References
Unpaired image-to-image translation aims to translate images from the source class to target one by providing sufficient data for these classes.
Tensor Low-Rank Reconstruction for Semantic Segmentation
Then we use these rank-1 tensors to recover the high-rank context features through our proposed tensor reconstruction module (TRM).
DSGN: Deep Stereo Geometry Network for 3D Object Detection
Most state-of-the-art 3D object detectors heavily rely on LiDAR sensors because there is a large performance gap between image-based and LiDAR-based methods.
An Adversarial Perturbation Oriented Domain Adaptation Approach for Semantic Segmentation
In contrast to adversarial alignment, we propose to explicitly train a domain-invariant classifier by generating and defensing against pointwise feature space adversarial perturbations.
Hierarchical Point-Edge Interaction Network for Point Cloud Semantic Segmentation
To incorporate point features in the edge branch, we establish a hierarchical graph framework, where the graph is initialized from a coarse layer and gradually enriched along the point decoding process.
Ranked #46 on
Semantic Segmentation
on S3DIS Area5
Reflective Decoding Network for Image Captioning
State-of-the-art image captioning methods mostly focus on improving visual features, less attention has been paid to utilizing the inherent properties of language to boost captioning performance.
Ranked #5 on
Image Captioning
on MS COCO
Non-local Recurrent Neural Memory for Supervised Sequence Modeling
Typical methods for supervised sequence modeling are built upon the recurrent neural networks to capture temporal dependencies.
Cross-Domain Adaptation for Animal Pose Estimation
Therefore, the easily available human pose dataset, which is of a much larger scale than our labeled animal dataset, provides important prior knowledge to boost up the performance on animal pose estimation.
Fast Point R-CNN
We present a unified, efficient and effective framework for point-cloud based 3D object detection.
SF-Net: Structured Feature Network for Continuous Sign Language Recognition
The proposed SF-Net extracts features in a structured manner and gradually encodes information at the frame level, the gloss level and the sentence level into the feature representation.
STD: Sparse-to-Dense 3D Object Detector for Point Cloud
We present a new two-stage 3D object detection framework, named sparse-to-dense 3D Object Detector (STD).
Attribute-Driven Spontaneous Motion in Unpaired Image Translation
Current image translation methods, albeit effective to produce high-quality results in various applications, still do not consider much geometric transform.
Landmark Assisted CycleGAN for Cartoon Face Generation
In this paper, we are interested in generating an cartoon face of a person by using unpaired training data between real faces and cartoon ones.
Region Refinement Network for Salient Object Detection
Albeit intensively studied, false prediction and unclear boundaries are still major issues of salient object detection.
2D Attentional Irregular Scene Text Recognizer
Irregular scene text, which has complex layout in 2D space, is challenging to most previous scene text recognizers.
Memory-Attended Recurrent Network for Video Captioning
Typical techniques for video captioning follow the encoder-decoder framework, which can only focus on one source video being processed.
Associatively Segmenting Instances and Semantics in Point Clouds
A 3D point cloud describes the real scene precisely and intuitively. To date how to segment diversified elements in such an informative 3D scene is rarely discussed.
Ranked #16 on
3D Instance Segmentation
on S3DIS
(mRec metric)
Human Pose Estimation with Spatial Contextual Information
With this principle, we present two conceptually simple and yet computational efficient modules, namely Cascade Prediction Fusion (CPF) and Pose Graph Neural Network (PGNN), to exploit underlying contextual information.
Ranked #10 on
Pose Estimation
on MPII Human Pose
IPOD: Intensive Point-based Object Detector for Point Cloud
We present a novel 3D object detection framework, named IPOD, based on raw point cloud.
Ranked #1 on
3D Object Detection
on KITTI Pedestrians Easy
Image Inpainting via Generative Multi-column Convolutional Neural Networks
In this paper, we propose a generative multi-column network for image inpainting.
Referring Image Segmentation via Recurrent Refinement Networks
We address the problem of image segmentation from natural language descriptions.
Facelet-Bank for Fast Portrait Manipulation
Digital face manipulation has become a popular and fascinating way to touch images with the prevalence of smartphones and social networks.
Scale-recurrent Network for Deep Image Deblurring
In single image deblurring, the "coarse-to-fine" scheme, i. e. gradually restoring the sharp image on different resolutions in a pyramid, is very successful in both traditional optimization-based methods and recent neural-network-based approaches.
Ranked #2 on
Image Deblurring
on GoPro
(Params (M) metric, using extra
training data)
Unsupervised Learning of Stereo Matching
However, due to the limitations of these datasets and the difficulty of collecting new stereo data, current methods fail in real-life cases.
Makeup-Go: Blind Reversion of Portrait Edit
In this paper, we propose the task of restoring a portrait image from this process.
Automatic Real-time Background Cut for Portrait Videos
A spatial-temporal refinement network is developed to further refine the segmentation errors in each frame and ensure temporal coherence in the segmentation map.
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
We focus on the challenging task of real-time semantic segmentation in this paper.
Ranked #12 on
Semantic Segmentation
on BDD100K val
Dichotomous Image Segmentation
Real-Time Semantic Segmentation
+3
Zero-order Reverse Filtering
In this paper, we study an unconventional but practically meaningful reversibility problem of commonly used image filters.
Convolutional Neural Pyramid for Image Processing
We propose a principled convolutional neural pyramid (CNP) framework for general low-level vision and image processing tasks.
High-Quality Correspondence and Segmentation Estimation for Dual-Lens Smart-Phone Portraits
Estimating correspondence between two images and extracting the foreground object are two challenges in computer vision.
Mutual-Structure for Joint Filtering
Previous joint/guided filters directly transfer the structural information in the reference image to the target one.
Deep LAC: Deep Localization, Alignment and Classification for Fine-Grained Recognition
Our major contribution is to propose a valve linkage function(VLF) for back-propagation chaining and form our deep localization, alignment and classification (LAC) system.
