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首页
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窄带高清
* 窄带高清
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视频云音频实验室HOT
Ali266视频编解码NEW
MediaBox音视频SDK WEB体验馆
视频云音频实验室
视频云音频实验室，专注于云-端，实时-离线，采集播放-分析-处理-传输等全面的音频技术，持续提升各个场景下的实时音频通信体验，为直播、点播、媒体生产提供丰富的音频分析处理能力。团队有机结合传统信号处理与深度学习技术，
致力于保障恶劣条件下的基础体验，提升极致体验，并为互联网音视频业务创造更多可能的玩法。
立即咨询
多媒体AI
多媒体AI（MultiMedia
AI）是视频云联合达摩院研发的视频AI通用技术平台产品，结合视觉及多模态技术，实现视频结构化、视频指纹搜索、视频生产等核心视频应用领域的基础功能，为客户在视频内容理解、版权保护、视频编目、视频搜索推荐、视频交互、视频辅助生产等应用场景种提供了核心能力，提高人员效率和流量效率。
立即咨询
视频云音频实验室
视频云音频实验室，专注于云-端，实时-离线，采集播放-分析-处理-传输等全面的音频技术，持续提升各个场景下的实时音频通信体验，为直播、点播、媒体生产提供丰富的音频分析处理能力。团队有机结合传统信号处理与深度学习技术，
致力于保障恶劣条件下的基础体验，提升极致体验，并为互联网音视频业务创造更多可能的玩法。
立即咨询
多媒体AI
多媒体AI（MultiMedia
AI）是视频云联合达摩院研发的视频AI通用技术平台产品，结合视觉及多模态技术，实现视频结构化、视频指纹搜索、视频生产等核心视频应用领域的基础功能，为客户在视频内容理解、版权保护、视频编目、视频搜索推荐、视频交互、视频辅助生产等应用场景种提供了核心能力，提高人员效率和流量效率。
立即咨询
*
*
视频云多媒体AI公有云能力
视频标签
通过对视频，语音，文本，图像等内容的多维理解，对多媒体进行结构化标签提取，可广泛应用于多媒体内容的管理、审核、搜索和推荐。
查看更多
视频搜索
视频内容检索用于音视频间相似片段搜索，通过深度模型理解视频，提取视频内容特征，建立视频搜索引擎。
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视频生产
对视频内容进行智能分析处理，支持横转竖、绿幕抠图、实景抠图、智能拆条等智能剪辑功能，提升视频剪辑效率。
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视频封面
通过对视频中语音，文本，图像等内容的理解，从丰富度，图像质量，精彩程度，吸引程度等多方面进行分析，形成封面。
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视频审核
识别多媒体文件中的违禁内容及质量问题，支持色情、暴恐、政治敏感、广告识别等违规内容审核。
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虚拟人
通过云计算、大数据和人工智能技术，提供虚拟人多模态交互解决方案，可广泛应用于传媒、娱乐和教育行业。
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窄带高清
从人眼视觉模型出发，针对视频画面场景、动作、内容、纹理等细节进行智能分析，实现在同等画质下更省流、在同等带宽下更高清的观看体验。
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视频增强修复
从视频清晰度、色彩、流畅性等维度进行综合提升，实现视频画质增强与问题修复，通过更高品质的视听内容提升用户体验。
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音频实验室
专注于云-端，实时-离线，采集播放-分析-处理-传输等全面的音频技术，提升各场景下的实时音频通信体验为直播、点播、媒体生产提供丰富的音频分析处理能力。
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我们的优势
多模态
利用视频、音频、文本等海量多模态数据，进行跨媒体理解，融合不同领域知识的理解/生产体系。
轻量化定制
用户可自主注册需要识别的实体，算法对新增实体标签可实现“即插即用”，且对新增类别使用轻量数据可接近已知类别效果。
高效能
自研高性能音视频编解码库、深度学习推理引擎、GPU预处理库，针对视频场景IO和计算密集型特点定向优化，在不同场景达到1到10倍性能提升。
通用性强
多媒体AI云产品在传媒行业、泛娱乐行业、短视频行业、体育行业以及电商行业等均有落地应用案例。
媒体报道
Alibaba’s AI Tool Makes Historical Paintings Blink, Smile and Speak
2021-09-28
Alibaba Group’s research arm DAMO Academy has used artificial intelligence to
make ancient Chinese portraits blink, smile and speak as part of a push to bring
cultural classics to life with digital technology. Last week, DAMO Academy
worked with a public library in Hangzhou, the company’s home city, to animate
about a dozen paintings from books in the library’s archives – including “The
Night Revels of Han Xizai” by artist Gu Hongzhong and illustrations in “Dream of
the Red Chamber” by Cao Xueqin.
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CCTV-13 新闻直播间 | 中秋假期 让传统文化“活”起来
2021-09-20
【 #AI让古代人开口吟中秋# 与现代人共聚】
古人是怎么过中秋的？最近杭州图书馆复现古人“吟咏”中秋的画面。如马远的《月夜拨阮图》、南唐顾闳中的《韩熙载夜宴图》，达摩院AI技术让插画中的人物模仿真人表情、开口说话并朗诵中秋题材的诗词，画中人的五官、神态也都会随之发生变化，展现细微表情。为了让大众参与古籍书画的传播，了解古代的风俗和传统文化，声音则是从市民中征集而来的。
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ICCV 2021 Oral | 阿里达摩院视觉实验室提出NGC：统一的开集带噪数据学习框架
2021-09-09
本篇工作中，作者及团队提出了一个开放场景下基于带噪数据的学习框架(NGC: A Unified Framework for Learning with
Open-World Noisy Data)，在训练与测试过程中均考虑了噪声样本的影响，在多个数据集上超过了当前SOTA方法。该方法在ICCV
2021上被接收为口头报告（Oral）。
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ICCV 2021 | 阿里达摩院视觉实验室提出OadTR框架，将Transformers引入在线行为检测任务
2021-09-09
本篇工作中，作者及团队解决的是在线行为检测任务，该任务旨在对于输入的在线视频流，识别出当前正在发生的行为类型（包括行为和背景）。最近，由于其在现实生活中具有巨大的应用前景，如自动驾驶，视频监控，异常行为检测等领域，
这项任务受到了越来越多的关注。 但是，这项任务存在只能关注到已经发生的一部分动作的难点，检测时未来信息是不可获得的。
此外，如何有效的聚合长程的时序依赖信息也是这项任务的难点之一。
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ICCV 2021 | 阿里达摩院视觉实验室提出SSCS：基于支持集的交叉监督的Video语言定位
2021-09-09
本篇工作中，作者及团队提出了一种基于支持集的交叉监督方法(support-set cross supervision, Sscs)。Sscs可以作为video
grounding任务的一个额外的分支，来更好的提取视频文本对中的相关信息。通过在一个视频和文本的特征共享空间中引入对比目标函数和生成目标函数，当两种模态的语义强相关时，两种模态的特征被强制变得相似。同时，为了解决实体之间的互斥问题，作者使用支持集来使得跨监督能更好地从整个视频中收集重要的视觉元素。实验表明，作者提出的Sscs仅在训练阶段使用，在推理阶段不增加额外计算量，显著提高state-of-the-art的性能。消融实验也验证了所提方法不同模块的有效性。
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ICCV 2021 | 阿里达摩院视觉实验室提出GAR：用于群体行为识别的动态时空推理网络
2021-09-09
本篇工作中，作者及团队提出了一种用于视频群体行为识别的动态时空推理网络(Spatio-Temporal Dynamic Inference Network
for Group Activity
Recognition)，在时空图的推理过程中引入可变形卷积的思想，通过在局部的时空交互域上对中心人物的全局交互图进行预测并更新特征，解决了之前在群体行为识别中可能出现的过平滑问题和计算量大的缺点。在同等实验设定下，推理模块只需要使用以往模型10%不到的计算量和参数量，便可以在两个业界权威数据集上达到最优结果。
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团队荣誉
* 冠军
ICCV 2021
2021-10-11
口罩人脸识别挑战赛WebFace260m SFR赛道
* 亚军
ICCV 2021
2021-10-11
口罩人脸识别挑战赛InsigtFace unconstrained赛道
* 季军
ICCV 2021
2021-10-11
口罩人脸识别挑战赛WebFace260m main赛道
* 季军
ICCV 2021
2021-10-11
口罩人脸识别挑战赛InsigtFace ms1m赛道
* 最佳论文展示奖
AICCOV 2021
2021-07-25
第二届中国光谷人工智能大会暨企业家高峰论坛
* 资质
自研多媒体智能理解平台
2021-06-16
通过具备CNAS和CMA资质的第三方认证
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