Ming焦点对战，杜兰特与40激战切尔西分钟，战术调整胜负难料！

xiaoyi1 2025-07-30 阅读:21 评论:9

来源：Google、iangoodfellow.com、新智元　　今天，2018年计算机视觉和模式识别会议（CVPR 2018）正在盐湖城举办，这是计算机视觉领域最重要的年度学术会议，包括主大会和若干workshop和tutorial。作为...

来源：Google、iangoodfellow.com、新智元

　　今天，2018年计算机视觉和模式识别会议（CVPR 2018）正在盐湖城举办，这是计算机视觉领域最重要的年度学术会议，包括主大会和若干workshop和tutorial。作为会议的钻石赞助商，谷歌在今年的CVPR上同样表现强势，有超过200名谷歌员工将在大会上展示论文或被邀请演讲，谷歌也组织和参与了多个研讨会。

　　根据谷歌官方博客，CVPR 2018谷歌共有45篇论文被接收。这些论文关注下一代智能系统和机器感知领域的最新机器学习技术，包括Pixel 2和Pixel 2 XL智能手机的人像模式背后的技术，V4版本的Open Images数据集等等。

　　Google at CVPR 2018

　　组织者

财务主席：Ramin Zabih

领域主席：Sameer Agarwal,爱游戏 Aseem Agrawala, Jon Barron, Abhinav Shrivastava, Carl Vondrick, Ming-Hsuan Yang

　　论文列表

Orals/Spotlights

　　作为结构表示的对象标志的无监督发现

　　Unsupervised Discovery of Object Landmarks as Structural Representations

　　Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee

　　DoubleFusion：利用单个深度传感器实时捕捉人体的内体形状

　　DoubleFusion:爱游戏入口 Real-time Capture of Human Performances with Inner Body Shapes from a Single Depth Sensor

　　Tao Yu, Zerong Zheng, Kaiwen Guo, Jianhui Zhao, Qionghai Dai, Hao Li, Gerard Pons-Moll, Yebin Liu

　　用于无监督运动重定向的神经运动网络

　　Neural Kinematic Networks for Unsupervised Motion Retargetting

　　Ruben Villegas, Jimei Yang, Duygu Ceylan, Honglak Lee

　　用核预测网络去噪

　　Burst Denoising with Kernel Prediction Networks

　　Ben Mildenhall, Jiawen Chen, Jonathan Barron, Robert Carroll, Dillon Sharlet, Ren Ng

　　神经网络的量化和训练，以实现高效的整数运算推理

　　Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

　　Benoit Jacob, Skirmantas Kligys, Bo Chen, Matthew Tang, Menglong Zhu, Andrew Howard, Dmitry Kalenichenko, Hartwig Adam

　　AVA：一个时空本地化原子视觉动作视频数据集

　　AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions

　　Chunhui Gu, Chen Sun, David Ross, Carl Vondrick, Caroline Pantofaru, Yeqing Li, Sudheendra Vijayanarasimhan, George Toderici, Susanna Ricco, Rahul Sukthankar, Cordelia Schmid, Jitendra Malik

　　视觉问答的视觉-文本注意力焦点

Ming焦点对战，杜兰特与40激战切尔西分钟，战术调整胜负难料！

　　Focal Visual-Text Attention for Visual Question Answering

　　Junwei Liang, Lu Jiang, Liangliang Cao, Li-Jia Li, Alexander G. Hauptmann

　　推断来自阴影中的光场

　　Inferring Light Fields from Shadows

　　Manel Baradad, Vickie Ye, Adam Yedida, Fredo Durand, William Freeman, Gregory Wornell, Antonio Torralba

　　修改多个视图中的非本地变量

　　Modifying Non-Local Variations Across Multiple Views

　　Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor

　　超越卷积的迭代视觉推理

　　Iterative Visual Reasoning Beyond Convolutions

　　Xinlei Chen, Li-jia Li, Fei-Fei Li, Abhinav Gupta

　　3D形变模型回归的无监督训练

　　Unsupervised Training for 3D Morphable Model Regression

　　Kyle Genova, Forrester Cole, Aaron Maschinot, Daniel Vlasic, Aaron Sarna, William Freeman

　　学习可扩展图像识别的可转换架构

　　Learning Transferable Architectures for Scalable Image Recognition

　　Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc Le

　　生物物种分类和检测数据集

　　The iNaturalist Species Classification and Detection Dataset

　　Grant van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, Serge Belongie

　　利用观察世界来学习内在的图像分解

　　Learning Intrinsic Image Decomposition from Watching the World

　　Zhengqi Li, Noah Snavely

　　学习智能对话框用于边界框注释

　　Learning Intelligent Dialogs for Bounding Box Annotation

　　Ksenia Konyushkova, Jasper Uijlings, Christoph Lampert, Vittorio Ferrari

Posters

　　重新审视训练对象类别检测器的知识迁移

　　Revisiting Knowledge Transfer for Training Object Class Detectors

　　Jasper Uijlings, Stefan Popov, Vittorio Ferrari

　　重新思考用Faster R-CNN架构进行时间动作定位

　　Rethinking the Faster R-CNN Architecture for Temporal Action Localization

　　Yu-Wei Chao, Sudheendra Vijayanarasimhan, Bryan Seybold, David Ross, Jia Deng, Rahul Sukthankar

　　视觉对象识别的层次式新颖性检测

　　Hierarchical Novelty Detection for Visual Object Recognition

　　Kibok Lee, Kimin Lee, Kyle Min, Yuting Zhang, Jinwoo Shin, Honglak Lee

　　COCO-Stuff：语境中的事物和材料类别

　　COCO-Stuff: Thing and Stuff Classes in Context

　　Holger Caesar, Jasper Uijlings, Vittorio Ferrari

　　用于视频分类的外观关系网络

　　Appearance-and-Relation Networks for Video Classification

　　Limin Wang, Wei Li, Wen Li, Luc Van Gool

　　MorphNet：深度网络的快速简单资源约束结构学习

　　MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks

　　Ariel Gordon, Elad Eban, Bo Chen, Ofir Nachum, Tien-Ju Yang, Edward Choi

　　图形卷积自动编码器的可变形形状补完

　　Deformable Shape Completion with Graph Convolutional Autoencoders

　　Or Litany, Alex Bronstein, Michael Bronstein, Ameesh Makadia

　　MegaDepth：从互联网照片学习单视图深度预测

　　MegaDepth: Learning Single-View Depth Prediction from Internet Photos

　　Zhengqi Li, Noah Snavely

　　作为结构表示的对象标志的无监督发现

　　Unsupervised Discovery of Object Landmarks as Structural Representations

　　Yuting Zhang, Yijie Guo, Yixin Jin, Yijun Luo, Zhiyuan He, Honglak Lee

　　用核预测网络去噪

　　Burst Denoising with Kernel Prediction Networks

　　Ben Mildenhall, Jiawen Chen, Jonathan Barron, Robert Carroll, Dillon Sharlet, Ren Ng

　　神经网络的量化和训练，以实现高效的整数运算推理

　　Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

　　Benoit Jacob, Skirmantas Kligys, Bo Chen, Matthew Tang, Menglong Zhu, Andrew Howard, Dmitry Kalenichenko, Hartwig Adam

　　Pix3D：单图像3D形状建模的数据集和方法

　　Pix3D: Dataset and Methods for Single-Image 3D Shape Modeling

　　Xingyuan Sun, Jiajun Wu, Xiuming Zhang, Zhoutong Zhang, Tianfan Xue, Joshua Tenenbaum,William Freeman

　　用于表示和编辑图像的稀疏智能轮廓

　　Sparse, Smart Contours to Represent and Edit Images

　　Tali Dekel, Dilip Krishnan, Chuang Gan, Ce Liu, William Freeman

　　MaskLab：通过使用语义和方向特征优化对象检测进行实例分割

　　MaskLab: Instance Segmentation by Refining Object Detection with Semantic and Direction Features

　　Liang-Chieh Chen, Alexander Hermans, George Papandreou, Florian Schroff, Peng Wang,Hartwig Adam

　　大规模细粒度分类和领域特定的迁移学习

　　Large Scale Fine-Grained Categorization and Domain-Specific Transfer Learning

　　Yin Cui, Yang Song, Chen Sun, Andrew Howard, Serge Belongie

　　改进的带有初始值和空间自适应比特率的有损网络压缩

　　Improved Lossy Image Compression with Priming and Spatially Adaptive Bit Rates for Recurrent Networks

　　Nick Johnston, Damien Vincent, David Minnen, Michele Covell, Saurabh Singh, Sung Jin Hwang, George Toderici, Troy Chinen, Joel Shor

　　MobileNetV2：反向残差和线性瓶颈

　　MobileNetV2: Inverted Residuals and Linear Bottlenecks

　　Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, Liang-Chieh Chen

　　ScanComplete：3D扫描的大规模场景补完和语义分割

　　ScanComplete: Large-Scale Scene Completion and Semantic Segmentation for 3D Scans

　　Angela Dai, Daniel Ritchie, Martin Bokeloh, Scott Reed, Juergen Sturm, Matthias Nießner

　　Sim2Real通过循环控制查看不变视觉伺服

　　Sim2Real View Invariant Visual Servoing by Recurrent Control

　　Fereshteh Sadeghi, Alexander Toshev, Eric Jang, Sergey Levine

　　Alternating-Stereo VINS：可观测性分析和性能评估

　　Alternating-Stereo VINS: Observability Analysis and Performance Evaluation

　　Mrinal Kanti Paul, Stergios Roumeliotis

　　桌上足球

　　Soccer on Your Tabletop

　　Konstantinos Rematas, Ira Kemelmacher, Brian Curless, Steve Seitz

　　使用3D几何约束从单眼视频中无监督地学习深度和自我爱游戏体育运动

　　Unsupervised Learning of Depth and Ego-Motion from Monocular Video Using 3D Geometric Constraints

　　Reza Mahjourian, Martin Wicke, Anelia Angelova

　　AVA：一个时空本地化原子视觉动作视频数据集

　　AVA: A Video Dataset of Spatio-temporally Localized Atomic Visual Actions

　　Chunhui Gu, Chen Sun, David Ross, Carl Vondrick, Caroline Pantofaru, Yeqing Li, Sudheendra Vijayanarasimhan, George Toderici, Susanna Ricco, Rahul Sukthankar, Cordelia Schmid, Jitendra Malik

　　推断来自阴影中的光场

　　Inferring Light Fields from Shadows

　　Manel Baradad, Vickie Ye, Adam Yedida, Fredo Durand, William Freeman, Gregory Wornell, Antonio Torralba

　　修改多个视图中的非本地变量

　　Modifying Non-Local Variations Across Multiple Views

　　Tal Tlusty, Tomer Michaeli, Tali Dekel, Lihi Zelnik-Manor

　　用于单目深度估计的孔径监控

　　Aperture Supervision for Monocular Depth Estimation

　　Pratul Srinivasan, Rahul Garg, Neal Wadhwa, Ren Ng, Jonathan Barron

　　实例嵌入转移到无监督视频对象分割

Ming焦点对战，杜兰特与40激战切尔西分钟，战术调整胜负难料！

　　Instance Embedding Transfer to Unsupervised Video Object Segmentation

　　Siyang Li, Bryan Seybold, Alexey Vorobyov, Alireza Fathi, Qin Huang, C.-C. Jay Kuo

　　帧回放视频超分辨率

　　Frame-Recurrent Video Super-Resolution

　　Mehdi S. M. Sajjadi, Raviteja Vemulapalli, Matthew Brown

　　稀疏时间池网络的弱监督动作定位

　　Weakly Supervised Action Localization by Sparse Temporal Pooling Network

　　Phuc Nguyen, Ting Liu, Gautam Prasad, Bohyung Han

　　超越卷积的迭代视觉推理

　　Iterative Visual Reasoning Beyond Convolutions

　　Xinlei Chen, Li-jia Li, Fei-Fei Li, Abhinav Gupta

　　学习和使用时间箭头

　　Learning and Using the Arrow of Time

　　Donglai Wei, Andrew Zisserman, William Freeman, Joseph Lim

　　HydraNets：高效推理的专用动态架构

　　HydraNets: Specialized Dynamic Architectures for Efficient Inference

　　Ravi Teja Mullapudi, Noam Shazeer, William Mark, Kayvon Fatahalian

　　在有限的监督下进行胸部疾病的识别和定位

　　Thoracic Disease Identification and Localization with Limited Supervision

　　Zhe Li, Chong Wang, Mei Han, Yuan Xue, Wei Wei, Li-jia Li, Fei-Fei Li

　　推断分层文本-图像合成的语义布局

　　Inferring Semantic Layout for Hierarchical Text-to-Image Synthesis

　　Seunghoon Hong, Dingdong Yang, Jongwook Choi, Honglak Lee

　　深层语义的脸部去模糊

　　Deep Semantic Face Deblurring

　　Ziyi Shen, Wei-Sheng Lai, Tingfa Xu, Jan Kautz, Ming-Hsuan Yang

　　3D形变模型回归的无监督训练

　　Unsupervised Training for 3D Morphable Model Regression

　　Kyle Genova, Forrester Cole, Aaron Maschinot, Daniel Vlasic, Aaron Sarna, William Freeman

　　学习可扩展图像识别的可转换架构

　　Learning Transferable Architectures for Scalable Image Recognition

　　Barret Zoph, Vijay Vasudevan, Jonathon Shlens, Quoc Le

　　利用观察世界来学习内在的图像分解

　　Learning Intrinsic Image Decomposition from Watching the World

　　Zhengqi Li, Noah Snavely

　　PiCANet：针对像素级的上下文注意力，以检测显著性

　　PiCANet: Learning Pixel-wise Contextual Attention for Saliency Detection

　　Nian Liu, Junwei Han, Ming-Hsuan Yang

Tutorials

　　机器人和驾驶中的计算机视觉

　　Computer Vision for Robotics and Driving

　　Anelia Angelova, Sanja Fidler

　　无监督视觉学习

　　Unsupervised Visual Learning

　　Pierre Sermanet, Anelia Angelova

　　UltraFast 3D感应，重建和理解人物、物体和环境

　　UltraFast 3D Sensing, Reconstruction and Understanding of People, Objects and Environments

　　Sean Fanello, Julien Valentin, Jonathan Taylor, Christoph Rhemann, Adarsh Kowdle, Jürgen Sturm, Christine Kaeser-Chen, Pavel Pidlypenskyi, Rohit Pandey, Andrea Tagliasacchi, Sameh Khamis, David Kim, Mingsong Dou, Kaiwen Guo, Danhang Tang, Shahram Izadi

　　生成对抗网络

　　Generative Adversarial Networks

　　Jun-Yan Zhu, Taesung Park, Mihaela Rosca, Phillip Isola, Ian Goodfellow

　　Ian Goodfellowa：生成对抗网络（35 PPT）

　　生成建模：密度估计

训练数据→密度函数

　　生成建模：样本生成

　　训练数据（CelebA）→样本生成

　　对抗网络的框架

　　Self-Attention GAN

　　ImageNet上最优的FID：1000个类别，128x128 像素

　　Self-Play