Titlebook: Computer Vision – ACCV 2018; 14th Asian Conferenc C. V. Jawahar,Hongdong Li,Konrad Schindler Conference proceedings 2019 Springer Nature Sw

小平面

Panorama from Representative Frames of Unconstrained Videos Using DiffeoMeshesgnment of the frames taken from a hand-held video is often very difficult to perform. The method proposed here aims to generate a panorama view of the video shot given as input. The proposed framework for panorama creation consists of four stages: The first stage performs a sparse frame selection ba

fiction

Robust and Efficient Ellipse Fitting Using Tangent Chord Distancemains unresolved due to many practical challenges such as occlusion, background clutter, noise and outlier, and so forth. In this paper, we introduce a novel geometric distance, called Tangent Chord Distance (TCD), to formulate the ellipse fitting problem. Under the least squares framework, TCD is u

客觀

尊敬

Bidirectional Conditional Generative Adversarial Networksnd known auxiliary information (.). We propose the Bidirectional cGAN (BiCoGAN), which effectively disentangles . and . in the generation process and provides an encoder that learns inverse mappings from . to both . and ., trained jointly with the generator and the discriminator. We present crucial

壓倒

Cross-Resolution Person Re-identification with Deep Antithetical Learningrson ReID model to handle the image resolution variations for improving its generalization ability. However, most existing person ReID methods pay little attention to this resolution discrepancy problem. One paradigm to deal with this problem is to use some complicated methods for mapping all images

減震

A Temporally-Aware Interpolation Network for Video Frame Inpaintingl video inpainting, frame interpolation, and video prediction. We devise a pipeline composed of two modules: a bidirectional video prediction module and a temporally-aware frame interpolation module. The prediction module makes two intermediate predictions of the missing frames, each conditioned on

Pelvic-Floor

GORGE

Indelible

Andris Ambainis,Mike Hamburg,Dominique Unruhing the remaining areas unaltered. To tackle this problem, we propose a two stage method, where each stage contains a generative adversarial network, that will alter the shape and style of objects in a subject image to reflect a donor image. We demonstrate the effectiveness of our method by transferring clothing between images.

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