“2022-02-21”版本间的差异
来自cslt Wiki
(6位用户的6个中间修订版本未显示) | |||
第5行: | 第5行: | ||
|Dong Wang | |Dong Wang | ||
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− | * | + | * Experiment on IB control with conditional model [http://192.168.0.51:5555/cgi-bin/cvss/cvss_request.pl?account=wangd&step=view_request&cvssid=847], rough conclusions were obtained. |
+ | * Refine the AV speaker recognition theoretical part. | ||
+ | * Review for ICME. | ||
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− | * | + | * Complete ICME review |
+ | * VQMIVC reproduction, update with random mask | ||
+ | * Some missing papers treatment: (1) true nonlinear LDA (2) CycleFlow (3) Thermal-visual database | ||
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第16行: | 第20行: | ||
|Yunqi Cai | |Yunqi Cai | ||
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− | * | + | *NSFC Application |
+ | *Materials inverse design investigation | ||
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第54行: | 第59行: | ||
|Haoran Sun | |Haoran Sun | ||
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− | * | + | * autoVC with cycle loss [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/1/16/Autovc-cyc.pdf pdf] [http://cslt.riit.tsinghua.edu.cn/mediawiki/images/6/66/Pre.rar demo] |
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− | * | + | * cycle loss after adverserial training |
+ | * VQMIVC | ||
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第77行: | 第83行: | ||
|Pengqi Li | |Pengqi Li | ||
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− | * | + | * collated the visualization methods that have been reproduced |
+ | * some scripts for baseline(cncsrc) | ||
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− | * | + | * study feature aggregation |
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第88行: | 第95行: | ||
|Weida Liang | |Weida Liang | ||
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+ | * Never-before-seen test [http://166.111.134.19:7777/liangwd/paper.html] | ||
* 3~6 spk cycle loss models on wav2vec+seq2seq model | * 3~6 spk cycle loss models on wav2vec+seq2seq model | ||
* Rewrite paper and focus on cycle loss | * Rewrite paper and focus on cycle loss | ||
第124行: | 第132行: | ||
*Find the baseline for CN-Celeb speaker identification | *Find the baseline for CN-Celeb speaker identification | ||
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− | *Train this baseline and find | + | *Train this baseline and find face recognition baseline |
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第144行: | 第152行: | ||
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* Check CKA | * Check CKA | ||
+ | * Do experiment for gender | ||
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− | * | + | * Do experiment for cross-modal PLDA |
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2022年2月21日 (一) 11:31的最后版本
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Dong Wang |
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Yunqi Cai |
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Lantian Li |
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Ying Shi |
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Haoran Sun |
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Chen Chen |
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Pengqi Li |
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Weida Liang |
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Zixi Yan |
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Sirui Li |
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Haoyu Jiang |
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Ruihai Hou |
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Renmiao Chen |
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