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Toward Accurate Post-Training Quantization for Image Super Resolution

https://doi.org/10.1109/cvpr52729.2023.00567

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/978-3-030-58548-8_6openalex-snapshot

Binarized Neural Network for Single Image Super Resolution

inferredcites →https://doi.org/10.1007/978-3-030-58595-2_34openalex-snapshot

PAMS: Quantized Super-Resolution via Parameterized Max Scale

inferredcites →https://doi.org/10.1007/978-3-030-67070-2_2openalex-snapshot

Residual Feature Distillation Network for Lightweight Image Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-031-19797-0_1openalex-snapshot

Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks

inferredcites →https://doi.org/10.1007/978-3-031-19830-4_5openalex-snapshot

Factorizing Knowledge in Neural Networks

inferredcites →https://doi.org/10.1007/978-3-031-20071-7_22openalex-snapshot

CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution

inferredcites →https://doi.org/10.1007/978-3-031-20083-0_23openalex-snapshot

AdaBin: Improving Binary Neural Networks with Adaptive Binary Sets

inferredcites →https://doi.org/10.1007/978-3-642-27413-8_47openalex-snapshot

On Single Image Scale-Up Using Sparse-Representations

inferredcites →https://doi.org/10.1016/j.sigpro.2009.09.002openalex-snapshot

A super-resolution reconstruction algorithm for surveillance images

inferredcites →https://doi.org/10.1038/s41928-019-0288-0openalex-snapshot

CMOS-integrated memristive non-volatile computing-in-memory for AI edge processors

inferredcites →https://doi.org/10.1049/ipr2.12359openalex-snapshot

Real‐world super‐resolution of face‐images from surveillance cameras

inferredcites →https://doi.org/10.1093/comjnl/bxm075openalex-snapshot

Super-Resolution in Medical Imaging

inferredcites →https://doi.org/10.1109/cvpr.2015.7299156openalex-snapshot

Single image super-resolution from transformed self-exemplars

inferredcites →https://doi.org/10.1109/cvpr.2017.19openalex-snapshot

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network

inferredcites →https://doi.org/10.1109/cvpr.2018.00286openalex-snapshot

Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference

inferredcites →https://doi.org/10.1109/cvpr.2019.00292openalex-snapshot

Fully Quantized Network for Object Detection

inferredcites →https://doi.org/10.1109/cvprw.2017.149openalex-snapshot

NTIRE 2017 Challenge on Single Image Super-Resolution: Methods and Results

inferredcites →https://doi.org/10.1109/cvprw.2017.151openalex-snapshot

Enhanced Deep Residual Networks for Single Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvprw.2019.00096openalex-snapshot

Efficient Super Resolution Using Binarized Neural Network

inferredcites →https://doi.org/10.1109/cvprw.2019.00184openalex-snapshot

The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery

inferredcites →https://doi.org/10.1109/cvprw53098.2021.00283openalex-snapshot

Anchor-based Plain Net for Mobile Image Super-Resolution

inferredcites →https://doi.org/10.1109/cvprw53098.2021.00286openalex-snapshot

Real-Time Quantized Image Super-Resolution on Mobile NPUs, Mobile AI 2021 Challenge: Report

inferredcites →https://doi.org/10.1109/cvprw56347.2022.00348openalex-snapshot

RenderSR: A Lightweight Super-Resolution Model for Mobile Gaming Upscaling

inferredcites →https://doi.org/10.1109/icassp40776.2020.9054019openalex-snapshot

Efficient Image Super Resolution Via Channel Discriminative Deep Neural Network Pruning

inferredcites →https://doi.org/10.1109/iccv.2001.937655openalex-snapshot

A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics

inferredcites →https://doi.org/10.1109/iccvw.2019.00104openalex-snapshot

OpenVINO Deep Learning Workbench: Comprehensive Analysis and Tuning of Neural Networks Inference

inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot

Image quality assessment: from error visibility to structural similarity

inferredcites →https://doi.org/10.1109/tip.2023.3315540openalex-snapshot

E2FIF: Push the Limit of Binarized Deep Imagery Super-Resolution Using End-to-End Full-Precision Information Flow

inferredcites →https://doi.org/10.1109/wacv51458.2022.00099openalex-snapshot

DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks

inferredcites →https://doi.org/10.1145/3474085.3475227openalex-snapshot

Fully Quantized Image Super-Resolution Networks

inferredcites →https://doi.org/10.1201/9781439819319-13openalex-snapshot

New Applications of Super-Resolution in Medical Imaging

inferredcites →https://doi.org/10.1609/aaai.v35i2.16263openalex-snapshot

Training Binary Neural Network without Batch Normalization for Image Super-Resolution

inferredcites →https://doi.org/10.24963/ijcai.2021/155openalex-snapshot

Towards Compact Single Image Super-Resolution via Contrastive Self-distillation

inferredcites →https://doi.org/10.3390/rs11131588openalex-snapshot

Satellite Image Super-Resolution via Multi-Scale Residual Deep Neural Network

inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-snapshot

Adam: A Method for Stochastic Optimization

inferredcites →https://doi.org/10.48550/arxiv.1510.00149openalex-snapshot

Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding

inferredcites →https://doi.org/10.48550/arxiv.1602.02830openalex-snapshot

Binarized Neural Networks: Training Deep Neural Networks with Weights and Activations Constrained to +1 or -1

inferredcites →https://doi.org/10.48550/arxiv.1612.03928openalex-snapshot

Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer

inferredcites →https://doi.org/10.48550/arxiv.1805.06085openalex-snapshot

PACT: Parameterized Clipping Activation for Quantized Neural Networks

inferredcites →https://doi.org/10.48550/arxiv.1907.10701openalex-snapshot

Benchmarking TPU, GPU, and CPU Platforms for Deep Learning

inferredcites →https://doi.org/10.48550/arxiv.2111.03759openalex-snapshot

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

inferredcites →https://doi.org/10.48550/arxiv.2207.07268openalex-snapshot

Lightweight Vision Transformer with Cross Feature Attention

inferredcites →https://doi.org/10.5244/c.26.135openalex-snapshot

Low-Complexity Single-Image Super-Resolution based on Nonnegative Neighbor Embedding

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4679125openalex-extracted

inferred← citeshttps://doi.org/10.1007/978-3-031-72684-2_24openalex-snapshot

PQ-SAM: Post-training Quantization for Segment Anything Model

inferred← citeshttps://doi.org/10.1007/978-3-031-73661-2_13openalex-snapshot

POCA: Post-training Quantization with Temporal Alignment for Codec Avatars

inferred← citeshttps://doi.org/10.1007/978-3-032-37095-2_10openalex-snapshot

TAQ: Static-Deployable Temporal-Aware Quantization for Real-World Video Super-Resolution

inferred← citeshttps://doi.org/10.1007/978-3-032-38189-7_20openalex-snapshot

Frequency-Aware Post-Training Quantization for Medical Image Denoising

inferred← citeshttps://doi.org/10.1007/978-981-92-4805-6_28openalex-snapshot

A Configurable Streaming Accelerator for LUT-Based Super-Resolution on FPGA

inferred← citeshttps://doi.org/10.1007/s00521-025-11268-5openalex-snapshot

AQRG: adaptive quantization reconstruction granularity for post-training quantization

inferred← citeshttps://doi.org/10.1007/s00530-026-02294-xopenalex-snapshot

GPLMv2: an edge-ready post-training quantization framework for deploying complex underwater image enhancement models

inferred← citeshttps://doi.org/10.1007/s11432-023-4181-0openalex-snapshot

Distribution-flexible subset quantization for post-quantizing super-resolution networks

inferred← citeshttps://doi.org/10.1007/s11760-025-04992-xopenalex-snapshot

Robust ternary quantization for lightweight image denoising

inferred← citeshttps://doi.org/10.1007/s44443-026-00526-8openalex-snapshot

DMNet: detail modulation network with gradient-texture guidance for lightweight image super-resolution

inferred← citeshttps://doi.org/10.1016/j.image.2024.117175openalex-snapshot

A ‘deep’ review of video super-resolution

inferred← citeshttps://doi.org/10.1016/j.measen.2026.102013openalex-snapshot

Tool wear prediction using multi-domain features and quantised attention embedded CNN

inferred← citeshttps://doi.org/10.1109/access.2024.3375120openalex-snapshot

Fast On-Device Learning Framework for Single-Image Super-Resolution

inferred← citeshttps://doi.org/10.1109/apccas67402.2025.11376667openalex-snapshot

Layer Sensitivity Mixed-Precision Quantization for Image Super-Resolution

inferred← citeshttps://doi.org/10.1109/cvprw63382.2024.00639openalex-snapshot

Learning Optimized Low-Light Image Enhancement for Edge Vision Tasks

inferred← citeshttps://doi.org/10.1109/icassp48485.2024.10446281openalex-snapshot

Edge Deployable Distributed Evolutionary Optimization based Calibration method for Neural Quantization

inferred← citeshttps://doi.org/10.1109/iccvw69036.2025.00592openalex-snapshot

RCENet: Recursive Concatenation and Enhancement Network for Real-Time Super-Resolution

inferred← citeshttps://doi.org/10.1109/tip.2026.3733352openalex-snapshot

Memory-Efficient High-Ratio Model Compression for Image Super-Resolution via Hybrid Hashing

inferred← citeshttps://doi.org/10.1109/tnnls.2024.3493155openalex-snapshot

I²NQ: Inter and Intra Nonuniform Quantization for Single Image Super-Resolution

inferred← citeshttps://doi.org/10.1109/tpami.2025.3528042openalex-snapshot

Towards Accurate Post-Training Quantization of Vision Transformers via Error Reduction

inferred← citeshttps://doi.org/10.1109/tpami.2025.3529927openalex-snapshot

Exploring Frequency-Inspired Optimization in Transformer for Efficient Single Image Super-Resolution

inferred← citeshttps://doi.org/10.1109/tpami.2025.3610466openalex-snapshot

I&S-ViT: An Inclusive & Stable Method for Post-Training ViTs Quantization

inferred← citeshttps://doi.org/10.1109/tpami.2026.3697683openalex-snapshot

QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks

inferred← citeshttps://doi.org/10.1145/3636534.3690698openalex-snapshot

Perceptual-Centric Image Super-Resolution using Heterogeneous Processors on Mobile Devices

inferred← citeshttps://doi.org/10.1145/3727648.3727786openalex-snapshot

Dynamic Activation Binarization for Accurate Network Compression

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BlockEdge: A Hybrid Blockchain Framework for Secure and Efficient Collaboration in EEC Environments

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Hybrid Solution Through Systematic Electrical Impedance Tomography Data Reduction and CNN Compression for Efficient Hand Gesture Recognition on Resource-Constrained IoT Devices

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S2Transformer: Exploring Sparsity in Remote Sensing Images for Efficient Super-Resolution

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