Search Results for author: Di Lin

Found 15 papers, 4 papers with code

MISF: Multi-level Interactive Siamese Filtering for High-Fidelity Image Inpainting

1 code implementation12 Mar 2022 Xiaoguang Li, Qing Guo, Di Lin, Ping Li, Wei Feng, Song Wang

As a result, the final method takes the advantage of effective semantic & image-level filling for high-fidelity inpainting.

Image Inpainting Image Restoration +1

Uncertainty-Aware Cascaded Dilation Filtering for High-Efficiency Deraining

1 code implementation7 Jan 2022 Qing Guo, Jingyang Sun, Felix Juefei-Xu, Lei Ma, Di Lin, Wei Feng, Song Wang

First, we propose the uncertainty-aware cascaded predictive filtering (UC-PFilt) that can identify the difficulties of reconstructing clean pixels via predicted kernels and remove the residual rain traces effectively.

Data Augmentation Single Image Deraining

Recurrent Feature Propagation and Edge Skip-Connections for Automatic Abdominal Organ Segmentation

no code implementations2 Jan 2022 Zefan Yang, Di Lin, Yi Wang

Automatic segmentation of abdominal organs in computed tomography (CT) images can support radiation therapy and image-guided surgery workflows.

Computed Tomography (CT) Semantic Segmentation

CarveNet: Carving Point-Block for Complex 3D Shape Completion

no code implementations28 Jul 2021 Qing Guo, Zhijie Wang, Felix Juefei-Xu, Di Lin, Lei Ma, Wei Feng, Yang Liu

3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e. g., high-curvature, concave/convex, and hollowed-out 3D shapes) and the unknown & diverse patterns of the partially available point clouds.

Data Augmentation Point Cloud Completion

RANet: Region Attention Network for Semantic Segmentation

1 code implementation NeurIPS 2020 Dingguo Shen, Yuanfeng Ji, Ping Li, Yi Wang, Di Lin

In contrast to the previous methods, RANet configures the information pathways between the pixels in different regions, enabling the region interaction to exchange the regional context for enhancing all of the pixels in the image.

Semantic Segmentation

PRSNet: Part Relation and Selection Network for Bone Age Assessment

no code implementations5 Sep 2019 Yuanfeng Ji, Hao Chen, Dan Lin, Xiaohua Wu, Di Lin

These kinds of information can be effectively captured by the relation of different anatomical parts of hand bone.

ZigZagNet: Fusing Top-Down and Bottom-Up Context for Object Segmentation

no code implementations CVPR 2019 Di Lin, Dingguo Shen, Siting Shen, Yuanfeng Ji, Dani Lischinski, Daniel Cohen-Or, Hui Huang

In this work, we introduce ZigZagNet, which aggregates a richer multi-context feature map by using not only dense top-down and bottom-up propagation, but also by introducing pathways crossing between different levels of the top-down and the bottom-up hierarchies, in a zig-zag fashion.

Instance Segmentation Semantic Segmentation

Multi-Scale Context Intertwining for Semantic Segmentation

no code implementations ECCV 2018 Di Lin, Yuanfeng Ji, Dani Lischinski, Daniel Cohen-Or, Hui Huang

Accurate semantic image segmentation requires the joint consideration of local appearance, semantic information, and global scene context.

Semantic Segmentation

Structure-aware Generative Network for 3D-Shape Modeling

1 code implementation12 Aug 2018 Zhijie Wu, Xiang Wang, Di Lin, Dani Lischinski, Daniel Cohen-Or, Hui Huang

The key idea is that during the analysis, the two branches exchange information between them, thereby learning the dependencies between structure and geometry and encoding two augmented features, which are then fused into a single latent code.

Graphics

Cascaded Feature Network for Semantic Segmentation of RGB-D Images

no code implementations ICCV 2017 Di Lin, Guangyong Chen, Daniel Cohen-Or, Pheng-Ann Heng, Hui Huang

Our approach is to use the available depth to split the image into layers with common visual characteristic of objects/scenes, or common "scene-resolution".

Semantic Segmentation

Learning to Aggregate Ordinal Labels by Maximizing Separating Width

no code implementations ICML 2017 Guangyong Chen, Shengyu Zhang, Di Lin, Hui Huang, Pheng Ann Heng

While crowdsourcing has been a cost and time efficient method to label massive samples, one critical issue is quality control, for which the key challenge is to infer the ground truth from noisy or even adversarial data by various users.

ScribbleSup: Scribble-Supervised Convolutional Networks for Semantic Segmentation

no code implementations CVPR 2016 Di Lin, Jifeng Dai, Jiaya Jia, Kaiming He, Jian Sun

Large-scale data is of crucial importance for learning semantic segmentation models, but annotating per-pixel masks is a tedious and inefficient procedure.

Semantic Segmentation

Deep LAC: Deep Localization, Alignment and Classification for Fine-Grained Recognition

no code implementations CVPR 2015 Di Lin, Xiaoyong Shen, Cewu Lu, Jiaya Jia

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.

Classification General Classification

Learning Important Spatial Pooling Regions for Scene Classification

no code implementations CVPR 2014 Di Lin, Cewu Lu, Renjie Liao, Jiaya Jia

We address the false response influence problem when learning and applying discriminative parts to construct the mid-level representation in scene classification.

Classification General Classification +1

Two-Class Weather Classification

no code implementations CVPR 2014 Cewu Lu, Di Lin, Jiaya Jia, Chi-Keung Tang

Given a single outdoor image, this paper proposes a collaborative learning approach for labeling it as either sunny or cloudy.

Classification General Classification

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