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20152023
most citedLarge-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55

53 citations · 123 across the 18 of their papers we have counts for

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Showing 2019Show all

11 papers · 1 filter

eess.IV2019

Spatial-Angular Interaction for Light Field Image Super-Resolution

Yingqian Wang, Longguang Wang, Jungang Yang +3

Light field (LF) cameras record both intensity and directions of light rays, and capture scenes from a number of viewpoints. Both information within each perspective (i.e., spatial…

cs.CV2019

A Neural Rendering Framework for Free-Viewpoint Relighting

Zhang Chen, Anpei Chen, Guli Zhang +4

We present a novel Relightable Neural Renderer (RNR) for simultaneous view synthesis and relighting using multi-view image inputs. Existing neural rendering (NR) does not explicitl…

eess.IV2019

Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware Fusion

Jing Jin, Junhui Hou, Jie Chen +3

A densely-sampled light field (LF) is highly desirable in various applications, such as 3-D reconstruction, post-capture refocusing and virtual reality. However, it is costly to ac…

cs.CV2019

Light Field Super-resolution via Attention-Guided Fusion of Hybrid Lenses

Jing Jin, Junhui Hou, Jie Chen +2

This paper explores the problem of reconstructing high-resolution light field (LF) images from hybrid lenses, including a high-resolution camera surrounded by multiple low-resoluti…

cs.CV2019

Learning Semantics-aware Distance Map with Semantics Layering Network for Amodal Instance Segmentation

Ziheng Zhang, Anpei Chen, Ling Xie +2

In this work, we demonstrate yet another approach to tackle the amodal segmentation problem. Specifically, we first introduce a new representation, namely a semantics-aware distanc…

cs.CV2019

Generic Multiview Visual Tracking

Minye Wu, Haibin Ling, Ning Bi +3

Recent progresses in visual tracking have greatly improved the tracking performance. However, challenges such as occlusion and view change remain obstacles in real world deployment…