{"total":62,"rows":[{"id":"2108.10257","title":"SwinIR: Image Restoration Using Swin Transformer","created":"2021-08-23","cited_by_count":1887,"area":null},{"id":"2101.11517","title":"Investigating Bi-Level Optimization for Learning and Vision from a Unified Perspective: A Survey and Beyond","created":"2021-01-27","cited_by_count":153,"area":null},{"id":"2105.10422","title":"LAPAR: Linearly-Assembled Pixel-Adaptive Regression Network for Single Image Super-Resolution and Beyond","created":"2021-05-21","cited_by_count":88,"area":null},{"id":"2209.11345","title":"Swin2SR: SwinV2 Transformer for Compressed Image Super-Resolution and Restoration","created":"2022-09-22","cited_by_count":73,"area":null},{"id":"2304.10244","title":"Omni Aggregation Networks for Lightweight Image Super-Resolution","created":"2023-04-20","cited_by_count":62,"area":null},{"id":"2101.09336","title":"A Comprehensive Survey on Hardware-Aware Neural Architecture Search","created":"2021-01-22","cited_by_count":61,"area":null},{"id":"2302.13800","title":"Spatially-Adaptive Feature Modulation for Efficient Image Super-Resolution","created":"2023-02-27","cited_by_count":57,"area":null},{"id":"2205.15175","title":"ShuffleMixer: An Efficient ConvNet for Image Super-Resolution","created":"2022-05-30","cited_by_count":45,"area":null},{"id":"2103.08357","title":"Learning Frequency-aware Dynamic Network for Efficient Super-Resolution","created":"2021-03-15","cited_by_count":36,"area":null},{"id":"2108.08910","title":"Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search","created":"2021-08-18","cited_by_count":34,"area":null},{"id":"2207.10345","title":"CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution","created":"2022-07-21","cited_by_count":27,"area":null},{"id":"2209.13131","title":"Hitchhiker's Guide to Super-Resolution: Introduction and Recent Advances","created":"2022-09-27","cited_by_count":22,"area":null},{"id":"2204.08913","title":"Self-Calibrated Efficient Transformer for Lightweight Super-Resolution","created":"2022-04-19","cited_by_count":20,"area":null},{"id":"2207.12577","title":"Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution","created":"2022-07-25","cited_by_count":20,"area":null},{"id":"2103.09404","title":"Collapsible Linear Blocks for Super-Efficient Super Resolution","created":"2021-03-17","cited_by_count":19,"area":null},{"id":"2112.04488","title":"A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution","created":"2021-12-08","cited_by_count":19,"area":null},{"id":"2108.08202","title":"Overfitting the Data: Compact Neural Video Delivery via Content-aware Feature Modulation","created":"2021-08-18","cited_by_count":15,"area":null},{"id":"2107.12679","title":"MFAGAN: A Compression Framework for Memory-Efficient On-Device Super-Resolution GAN","created":"2021-07-27","cited_by_count":14,"area":null},{"id":"2405.20725","title":"GI-NAS: Boosting Gradient Inversion Attacks Through Adaptive Neural Architecture Search","created":"2024-05-31","cited_by_count":14,"area":null},{"id":"2212.14181","title":"Efficient Image Super-Resolution with Feature Interaction Weighted Hybrid Network","created":"2022-12-29","cited_by_count":13,"area":null},{"id":"2204.12266","title":"Attentive Fine-Grained Structured Sparsity for Image Restoration","created":"2022-04-26","cited_by_count":12,"area":null},{"id":"2209.12406","title":"A heterogeneous group CNN for image super-resolution","created":"2022-09-26","cited_by_count":11,"area":null},{"id":"2303.09190","title":"Resolution Enhancement Processing on Low Quality Images Using Swin Transformer Based on Interval Dense Connection Strategy","created":"2023-03-16","cited_by_count":9,"area":null},{"id":"2404.03296","title":"AdaBM: On-the-Fly Adaptive Bit Mapping for Image Super-Resolution","created":"2024-04-04","cited_by_count":9,"area":null},{"id":"2101.08525","title":"GhostSR: Learning Ghost Features for Efficient Image Super-Resolution","created":"2021-01-21","cited_by_count":8,"area":null},{"id":"2211.16776","title":"From Coarse to Fine: Hierarchical Pixel Integration for Lightweight Image Super-Resolution","created":"2022-11-30","cited_by_count":8,"area":null},{"id":"2205.14548","title":"Image Super-resolution with An Enhanced Group Convolutional Neural Network","created":"2022-05-29","cited_by_count":7,"area":null},{"id":"2210.07598","title":"Lightweight Stepless Super-Resolution of Remote Sensing Images via Saliency-Aware Dynamic Routing Strategy","created":"2022-10-14","cited_by_count":6,"area":null},{"id":"2101.04287","title":"3D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classification","created":"2021-01-12","cited_by_count":5,"area":null},{"id":"2105.03939","title":"Differentiable Neural Architecture Search for Extremely Lightweight Image Super-Resolution","created":"2021-05-09","cited_by_count":5,"area":null},{"id":"2307.13337","title":"Overcoming Distribution Mismatch in Quantizing Image Super-Resolution Networks","created":"2023-07-25","cited_by_count":5,"area":null},{"id":"2312.06101","title":"Hundred-Kilobyte Lookup Tables for Efficient Single-Image Super-Resolution","created":"2023-12-11","cited_by_count":5,"area":null},{"id":"2409.14330","title":"Thinking in Granularity: Dynamic Quantization for Image Super-Resolution by Intriguing Multi-Granularity Clues","created":"2024-09-22","cited_by_count":5,"area":null},{"id":"2104.09048","title":"Neural Architecture Search for Image Super-Resolution Using Densely Constructed Search Space: DeCoNAS","created":"2021-04-19","cited_by_count":4,"area":null},{"id":"2302.14557","title":"GRAN: Ghost Residual Attention Network for Single Image Super Resolution","created":"2023-02-28","cited_by_count":3,"area":null},{"id":"2104.02525","title":"Searching Efficient Model-guided Deep Network for Image Denoising","created":"2021-04-06","cited_by_count":2,"area":null},{"id":"2111.03524","title":"A Data-driven Approach to Neural Architecture Search Initialization","created":"2021-11-05","cited_by_count":2,"area":null},{"id":"2208.12484","title":"Laplacian Pyramid-like Autoencoder","created":"2022-08-26","cited_by_count":2,"area":null},{"id":"2212.07613","title":"DCS-RISR: Dynamic Channel Splitting for Efficient Real-world Image Super-Resolution","created":"2022-12-15","cited_by_count":2,"area":null},{"id":"2307.07240","title":"MaxSR: Image Super-Resolution Using Improved MaxViT","created":"2023-07-14","cited_by_count":2,"area":null},{"id":"2310.10413","title":"Image super-resolution via dynamic network","created":"2023-10-16","cited_by_count":2,"area":null},{"id":"2401.08913","title":"Efficient Image Super-Resolution via Symmetric Visual Attention Network","created":"2024-01-17","cited_by_count":2,"area":null},{"id":"2212.09501","title":"NAWQ-SR: A Hybrid-Precision NPU Engine for Efficient On-Device Super-Resolution","created":"2022-12-15","cited_by_count":1,"area":null},{"id":"2310.09525","title":"TS-ENAS:Two-Stage Evolution for Cell-based Network Architecture Search","created":"2023-10-14","cited_by_count":1,"area":null},{"id":"2405.09353","title":"Large coordinate kernel attention network for lightweight image super-resolution","created":"2024-05-15","cited_by_count":1,"area":null},{"id":"2509.22692","title":"Deep Learning Empowered Super-Resolution: A Comprehensive Survey and Future Prospects","created":"2025-09-19","cited_by_count":1,"area":null},{"id":"2106.06996","title":"Pyramidal Dense Attention Networks for Lightweight Image Super-Resolution","created":"2021-06-13","cited_by_count":0,"area":null},{"id":"2203.01994","title":"Fast Neural Architecture Search for Lightweight Dense Prediction Networks","created":"2022-03-03","cited_by_count":0,"area":null},{"id":"2207.01075","title":"Training Patch Analysis and Mining Skills for Image Restoration Deep Neural Networks","created":"2022-07-03","cited_by_count":0,"area":null},{"id":"2210.12257","title":"Efficient Automatic Machine Learning via Design Graphs","created":"2022-10-21","cited_by_count":0,"area":null},{"id":"2211.05773","title":"Scaling Neural Face Synthesis to High FPS and Low Latency by Neural Caching","created":"2022-11-10","cited_by_count":0,"area":null},{"id":"2212.06368","title":"Single Cell Training on Architecture Search for Image Denoising","created":"2022-12-13","cited_by_count":0,"area":null},{"id":"2303.08999","title":"A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU","created":"2023-03-16","cited_by_count":0,"area":null},{"id":"2307.09099","title":"A Survey on Multi-Objective Neural Architecture Search","created":"2023-07-18","cited_by_count":0,"area":null},{"id":"2408.09940","title":"ML-CrAIST: Multi-scale Low-high Frequency Information-based Cross black Attention with Image Super-resolving Transformer","created":"2024-08-19","cited_by_count":0,"area":null},{"id":"2409.06206","title":"AgileIR: Memory-Efficient Group Shifted Windows Attention for Agile Image Restoration","created":"2024-09-10","cited_by_count":0,"area":null},{"id":"2409.16947","title":"NTIRE 2024 Challenge on Stereo Image Super-Resolution: Methods and Results","created":"2024-09-25","cited_by_count":0,"area":null},{"id":"2412.02234","title":"CubeFormer: A Simple yet Effective Baseline for Lightweight Image Super-Resolution","created":"2024-12-03","cited_by_count":0,"area":null},{"id":"2503.14779","title":"Involution and BSConv Multi-Depth Distillation Network for Lightweight Image Super-Resolution","created":"2025-03-18","cited_by_count":0,"area":null},{"id":"2504.15649","title":"RepNet-VSR: Reparameterizable Architecture for High-Fidelity Video Super-Resolution","created":"2025-04-22","cited_by_count":0,"area":null},{"id":"2605.22351","title":"QuantSR+: Pushing the Limit of Quantized Image Super-Resolution Networks","created":"2026-05-21","cited_by_count":0,"area":null},{"id":"2605.25892","title":"SP-MoMamba: Superpixel-driven Mixture of State Space Experts for Efficient Image Super-Resolution","created":"2026-05-25","cited_by_count":0,"area":null}],"next_cursor":null}