Super Resolution
- A Layer-Wise Extreme Network Compression for Super Resolution
- Aligned Structured Sparsity Learning for Efficient Image Super-Resolution
- Binarized Neural Network for Single Image Super Resolution
- Fully !antized Image Super-Resolution Networks
- PAMS: Quantized Super-Resolution via Parameterized Max Scale
- Deep Learning for Image Super-resolution: A Survey
- Training Binary Neural Network without Batch Normalization for Image Super-Resolution
- Video super‑resolution based on deep learning: a comprehensive survey
- BasicVSR: The Search for Essential Components in Video Super-Resolution and Beyond
- Enhanced Deep Residual Networks for Single Image Super-Resolution
- Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile Devices
- CADyQ: Content-Aware Dynamic Quantization for Image Super-Resolution
- Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution
- Dynamic Dual Trainable Bounds for Ultra-low Precision Super-Resolution Networks
- Adaptive Patch Exiting for Scalable Single Image Super-Resolution
- Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search
- Learning Efficient Image Super-Resolution Networks via Structure-Regularized Pruning
- Fine-grained neural architecture search for image super-resolution
- Fast and Memory-Efficient Network Towards Efficient Image Super-Resolution
- DAQ: Channel-Wise Distribution-Aware Quantization for Deep Image Super-Resolution Networks
- Wide Activation for Efficient and Accurate Image Super-Resolution