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Pengchong Jin

4 accepted papers

2021

COMISR: Compression-Informed Video Super-Resolution

ICCV 2021poster

Most video super-resolution methods focus on restoring high-resolution video frames from low-resolution videos without taking into account compression. However, most videos on the web or mobile devices are compressed, and the compression can be severe when the bandwidth is limited. In this paper, we…

Cited by 48PDFcodeScholar
2020

BigNAS: Scaling Up Neural Architecture Search with Big Single-Stage Models

ECCV 2020poster

Neural architecture search (NAS) methods have shown promising results discovering models that are both accurate and fast. For NAS, training a one-shot model has became a popular strategy to rank the relative quality of different architectures (child models) using a single set of shared weights. Howe…

Cited by 358SourcePDFScholar
2020

Efficient Scale-Permuted Backbone with Learned Resource Distribution

ECCV 2020poster

Recently, SpineNet has demonstrated promising results on object detection and image classification over ResNet model. However, it is unclear if the improvement adds up when combining scale-permuted backbone with advanced efficient operations and compound scaling. Furthermore, SpineNet is built with…

Cited by 4SourcePDFScholar
2020

SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization

CVPR 2020poster

Convolutional neural networks typically encode an input image into a series of intermediate features with decreasing resolutions. While this structure is suited to classification tasks, it does not perform well for tasks requiring simultaneous recognition and localization (e.g., object detection). T…

Cited by 259PDFcodeScholar