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06/08/2023
FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow
This paper introduces a novel transformer-based network architecture, Fl...
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03/15/2023
VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation
We introduce VideoFlow, a novel optical flow estimation framework for vi...
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03/06/2023
KBNet: Kernel Basis Network for Image Restoration
How to aggregate spatial information plays an essential role in learning...
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03/02/2023
FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation
FlowFormer introduces a transformer architecture into optical flow estim...
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08/10/2022
Learning Degradation Representations for Image Deblurring
In various learning-based image restoration tasks, such as image denoisi...
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07/29/2022
Evaluating the Practicality of Learned Image Compression
Learned image compression has achieved extraordinary rate-distortion per...
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06/22/2022
No Attention is Needed: Grouped Spatial-temporal Shift for Simple and Efficient Video Restorers
Video restoration, aiming at restoring clear frames from degraded videos...
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05/10/2022
Efficient Burst Raw Denoising with Variance Stabilization and Multi-frequency Denoising Network
With the growing popularity of smartphones, capturing high-quality image...
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03/30/2022
Practical Learned Lossless JPEG Recompression with Multi-Level Cross-Channel Entropy Model in the DCT Domain
JPEG is a popular image compression method widely used by individuals, d...
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03/30/2022
FlowFormer: A Transformer Architecture for Optical Flow
We introduce Optical Flow TransFormer (FlowFormer), a transformer-based ...
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03/21/2022
ELIC: Efficient Learned Image Compression with Unevenly Grouped Space-Channel Contextual Adaptive Coding
Recently, learned image compression techniques have achieved remarkable ...
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02/15/2022
Post-Training Quantization for Cross-Platform Learned Image Compression
It has been witnessed that learned image compression has outperformed co...
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11/29/2021
IDR: Self-Supervised Image Denoising via Iterative Data Refinement
The lack of large-scale noisy-clean image pairs restricts supervised den...
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10/10/2021
Rethinking Noise Synthesis and Modeling in Raw Denoising
The lack of large-scale real raw image denoising dataset gives rise to c...
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03/29/2021
Checkerboard Context Model for Efficient Learned Image Compression
For learned image compression, the autoregressive context model is prove...
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01/14/2020
Cross-dataset Training for Class Increasing Object Detection
We present a conceptually simple, flexible and general framework for cro...
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05/06/2018
Quantization Mimic: Towards Very Tiny CNN for Object Detection
In this paper, we propose a simple and general framework for training ve...
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12/16/2017
Impression Network for Video Object Detection
Video object detection is more challenging compared to image object dete...
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06/29/2017