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Model Compression

1674 directly classified papers

Papers per year

Papers

DECORE: Deep Compression With Reinforcement Learning CVPR 2022
Attentive Fine-Grained Structured Sparsity for Image Restoration CVPR 2022
DeeCap: Dynamic Early Exiting for Efficient Image Captioning CVPR 2022
PCA-Based Knowledge Distillation Towards Lightweight and Content-Style Balanced Photorealistic Style Transfer Models CVPR 2022
3DAC: Learning Attribute Compression for Point Clouds CVPR 2022
Instance-Aware Dynamic Neural Network Quantization CVPR 2022
When To Prune? A Policy Towards Early Structural Pruning CVPR 2022
Lite Pose: Efficient Architecture Design for 2D Human Pose Estimation CVPR 2022
Compressing Models With Few Samples: Mimicking Then Replacing CVPR 2022
Symbolic Distillation for Learned TCP Congestion Control NIPS 2022
Structural Pruning via Latency-Saliency Knapsack NIPS 2022
VTC-LFC: Vision Transformer Compression with Low-Frequency Components NIPS 2022
Deep Compression of Pre-trained Transformer Models NIPS 2022
BiT: Robustly Binarized Multi-distilled Transformer NIPS 2022
projUNN: efficient method for training deep networks with unitary matrices NIPS 2022
Rare Gems: Finding Lottery Tickets at Initialization NIPS 2022
FP8 Quantization: The Power of the Exponent NIPS 2022
Compressible-composable NeRF via Rank-residual Decomposition NIPS 2022
Advancing Model Pruning via Bi-level Optimization NIPS 2022
UDC: Unified DNAS for Compressible TinyML Models for Neural Processing Units NIPS 2022
Lottery Tickets on a Data Diet: Finding Initializations with Sparse Trainable Networks NIPS 2022
Layer Freezing & Data Sieving: Missing Pieces of a Generic Framework for Sparse Training NIPS 2022
Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations NIPS 2022
Towards Efficient 3D Object Detection with Knowledge Distillation NIPS 2022
Entropy-Driven Mixed-Precision Quantization for Deep Network Design NIPS 2022