2 citations · 3 across the 9 of their papers we have counts for
9 papers
RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution
Biao Wu, Diankai Zhang, Shaoli Liu +3
As a fundamental challenge in visual computing, video super-resolution (VSR) focuses on reconstructing highdefinition video sequences from their degraded lowresolution counterparts…
USM RNN-T model weights binarization
Oleg Rybakov, Dmitriy Serdyuk, Chengjian Zheng
Large-scale universal speech models (USM) are already used in production. However, as the model size grows, the serving cost grows too. Serving cost of large models is dominated by…
Semi-supervised Video Semantic Segmentation Using Unreliable Pseudo Labels for PVUW2024
Biao Wu, Diankai Zhang, Si Gao +3
Pixel-level Scene Understanding is one of the fundamental problems in computer vision, which aims at recognizing object classes, masks and semantics of each pixel in the given imag…
2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation
Biao Wu, Diankai Zhang, Si Gao +3
Video Panoptic Segmentation (VPS) is a challenging task that is extends from image panoptic segmentation.VPS aims to simultaneously classify, track, segment all objects in a video,…
Real-Time 4K Super-Resolution of Compressed AVIF Images. AIS 2024 Challenge Survey
Marcos V. Conde, Zhijun Lei, Wen Li +72
This paper introduces a novel benchmark as part of the AIS 2024 Real-Time Image Super-Resolution (RTSR) Challenge, which aims to upscale compressed images from 540p to 4K resolutio…
Recyclable Semi-supervised Method Based on Multi-model Ensemble for Video Scene Parsing
Biao Wu, Shaoli Liu, Diankai Zhang +4
Pixel-level Scene Understanding is one of the fundamental problems in computer vision, which aims at recognizing object classes, masks and semantics of each pixel in the given imag…
Power Efficient Video Super-Resolution on Mobile NPUs with Deep Learning, Mobile AI & AIM 2022 challenge: Report
Andrey Ignatov, Radu Timofte, Cheng-Ming Chiang +50
Video super-resolution is one of the most popular tasks on mobile devices, being widely used for an automatic improvement of low-bitrate and low-resolution video streams. While num…
Accelerating RNN-T Training and Inference Using CTC guidance
Yongqiang Wang, Zhehuai Chen, Chengjian Zheng +3
We propose a novel method to accelerate training and inference process of recurrent neural network transducer (RNN-T) based on the guidance from a co-trained connectionist temporal…
NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video: Dataset, Methods and Results
Ren Yang, Radu Timofte, Meisong Zheng +75
This paper reviews the NTIRE 2022 Challenge on Super-Resolution and Quality Enhancement of Compressed Video. In this challenge, we proposed the LDV 2.0 dataset, which includes the…