找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Computer Vision – ECCV 2018; 15th European Confer Vittorio Ferrari,Martial Hebert,Yair Weiss Conference proceedings 2018 Springer Nature Sw

[復(fù)制鏈接]
樓主: 相持不下
51#
發(fā)表于 2025-3-30 11:48:18 | 只看該作者
52#
發(fā)表于 2025-3-30 15:39:30 | 只看該作者
Super-Identity Convolutional Neural Network for Face Hallucinationy information. However, previous face hallucination approaches largely ignore facial identity recovery. This paper proposes Super-Identity Convolutional Neural Network (SICNN) to recover identity information for generating faces closed to the real identity. Specifically, we define a super-identity l
53#
發(fā)表于 2025-3-30 17:00:10 | 只看該作者
What Do I Annotate Next? An Empirical Study of Active Learning for Action Localizationdata is scarce. In this paper, we introduce a novel active learning framework for temporal localization that aims to mitigate this data dependency issue. We equip our framework with active selection functions that can . from previously annotated datasets. We study the performance of two state-of-the
54#
發(fā)表于 2025-3-30 21:40:14 | 只看該作者
Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3essions, poses, and illuminations conditioned by synthetic images sampled from a 3D morphable model. Previous adversarial style-transfer methods either supervise their networks with a large volume of paired data or train highly under-constrained two-way generative networks in an unsupervised fashion
55#
發(fā)表于 2025-3-31 01:37:05 | 只看該作者
56#
發(fā)表于 2025-3-31 08:27:03 | 只看該作者
Neural Network Encapsulation which resemble lower counterparts in the higher layer should be activated. However, the computational complexity becomes a bottleneck for scaling up to larger networks, as lower capsules need to correspond to each and every higher capsule. To resolve this limitation, we approximate the routing proc
57#
發(fā)表于 2025-3-31 11:38:47 | 只看該作者
58#
發(fā)表于 2025-3-31 15:00:23 | 只看該作者
Integrating Egocentric Videos in Top-View Surveillance Videos: Joint Identification and Temporal Aliy with videos captured by top-view surveillance cameras. In this paper, we aim to relate these two sources of information from a surveillance standpoint, namely in terms of identification and temporal alignment. Given an egocentric video and a top-view video, our goals are to: (a) identify the egoce
59#
發(fā)表于 2025-3-31 21:07:53 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 12:59
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
峨眉山市| 麻阳| 思南县| 松溪县| 安丘市| 获嘉县| 贵港市| 黎川县| 高平市| 和田县| 南靖县| 青川县| 三江| 宜都市| 贺兰县| 彭泽县| 松桃| 凤城市| 靖西县| 盐池县| 朔州市| 凤城市| 平和县| 龙口市| 工布江达县| 喀什市| 九龙城区| 文成县| 南康市| 东兰县| 万山特区| 湖北省| 潍坊市| 平舆县| 福鼎市| 苍山县| 桂阳县| 长顺县| 漯河市| 胶州市| 克什克腾旗|