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20212023
most citedRethinking Benchmarks for Cross-modal Image-text Retrieval

24 citations · 65 across the 15 of their papers we have counts for

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Showing 2022Show all

6 papers · 1 filter

cs.CV2022

CapEnrich: Enriching Caption Semantics for Web Images via Cross-modal Pre-trained Knowledge

Linli Yao, Weijing Chen, Qin Jin

Automatically generating textual descriptions for massive unlabeled images on the web can greatly benefit realistic web applications, e.g. multimodal retrieval and recommendation.…

cs.CV2022★ 9 cited

TS2-Net: Token Shift and Selection Transformer for Text-Video Retrieval

Yuqi Liu, Pengfei Xiong, Luhui Xu +2

Text-Video retrieval is a task of great practical value and has received increasing attention, among which learning spatial-temporal video representation is one of the research hot…

cs.SD2022

Muskits: an End-to-End Music Processing Toolkit for Singing Voice Synthesis

Jiatong Shi, Shuai Guo, Tao Qian +9

This paper introduces a new open-source platform named Muskits for end-to-end music processing, which mainly focuses on end-to-end singing voice synthesis (E2E-SVS). Muskits suppor…

cs.CL2022★ 5 cited

Generalizing Multimodal Pre-training into Multilingual via Language Acquisition

Liang Zhang, Anwen Hu, Qin Jin

English-based Vision-Language Pre-training (VLP) has achieved great success in various downstream tasks. Some efforts have been taken to generalize this success to non-English lang…

cs.CL2022

M3ED: Multi-modal Multi-scene Multi-label Emotional Dialogue Database

Jinming Zhao, Tenggan Zhang, Jingwen Hu +4

The emotional state of a speaker can be influenced by many different factors in dialogues, such as dialogue scene, dialogue topic, and interlocutor stimulus. The currently availabl…

eess.AS2022

SingAug: Data Augmentation for Singing Voice Synthesis with Cycle-consistent Training Strategy

Shuai Guo, Jiatong Shi, Tao Qian +2

Deep learning based singing voice synthesis (SVS) systems have been demonstrated to flexibly generate singing with better qualities, compared to conventional statistical parametric…