| Rethinking Dataset Distillation for Classification: Do Distilled Sets Outperform Coresets? added by Syntology |
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| EndoCaver: Handling Fog, Blur and Glare in Endoscopic Images via Joint Deblurring-Segmentation added by Syntology |
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ReaganWu/EndoCaver/endocaver/model.py 905aac0dbd683010 |
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| arXiv:2507.06482 |
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hwang52/FedDifRC/model/mobilenetv2.py a0131fb70c267a9e |
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| Reprogramming Distillation for Medical Foundation Models |
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MediaBrain-SJTU/RD/network/mobilenet_v2.py ea8083eb90046a26 |
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| DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models |
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| Auto-Train-Once: Controller Network Guided Automatic Network Pruning from Scratch |
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| Knowledge Distillation Based on Transformed Teacher Matching |
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| I-SplitEE: Image classification in Split Computing DNNs with Early Exits |
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| SBCFormer: Lightweight Network Capable of Full-size ImageNet Classification at 1 FPS on Single Board Computers |
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xyonglu/sbcformer/models/mobilenetv2.py a0131fb70c267a9e |
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| Solving Oscillation Problem in Post-Training Quantization Through a Theoretical Perspective |
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| Three Guidelines You Should Know for Universally Slimmable Self-Supervised Learning |
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| Curriculum Temperature for Knowledge Distillation |
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| Switchable Online Knowledge Distillation |
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| Knowledge Distillation Meets Open-Set Semi-Supervised Learning |
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| Class-Incremental Learning for Action Recognition in Videos |
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mit-han-lab/temporal-shift-module/archs/mobilenet_v2.py a0131fb70c267a9e |
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| Knowledge Distillation as Efficient Pre-training: Faster Convergence, Higher Data-efficiency, and Better Transferability |
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| CLIP-Lite: Information Efficient Visual Representation Learning with Language Supervision |
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| Training Deep Neural Networks with Adaptive Momentum Inspired by the Quadratic Optimization |
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kentaroy47/vision-transformers-cifar10/models/mobilevit.py 3fb34464dacbb0d3 |
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| MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer |
5 Oct 2021 |
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| MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer |
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chinhsuanwu/mobilevit-pytorch/mobilevit.py 3fb34464dacbb0d3 |
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| MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer |
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kornia/kornia/kornia/models/vit_mobile.py 564f22f3b28db627 |
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| MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer |
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chinhsuanwu/mobilevit-pytorch/mobilevit.py 248f0c82db73b84d |
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| Simon Says: Evaluating and Mitigating Bias in Pruned Neural Networks with Knowledge Distillation |
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codestar12/pruning-distilation-bias/models/mobilenetv2.py 7765583b9e540679 |
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| Zero-Cost Operation Scoring in Differentiable Architecture Search |
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zerocostptnas/zerocost_operation_score/mobilenet_search_space/retrain_architecture/model.py a0131fb70c267a9e |
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| BERT Learns to Teach: Knowledge Distillation with Meta Learning |
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JetRunner/MetaDistil/cv/models/mobilenetv2.py 7765583b9e540679 |
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| CT-Net: Channel Tensorization Network for Video Classification |
3 Jun 2021 |
Andy1621/CT-Net/ops/reshape_block.py c455a6669e2554a5 |
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| EfficientNetV2: Smaller Models and Faster Training |
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d-li14/efficientnetv2.pytorch/effnetv2.py 15be99ad0bcca709 |
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| Differential Viewpoints for Ground Terrain Material Recognition |
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jiaxue1993/pytorch-material-classification/model/mobilenet_v2.py a0131fb70c267a9e |
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| Towards Fast, Accurate and Stable 3D Dense Face Alignment |
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cleardusk/3DDFA_V2/models/mobilenet_v3.py db82a4013a44fb42 |
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| Rethinking Bottleneck Structure for Efficient Mobile Network Design |
5 Jul 2020 |
zhoudaquan/rethinking_bottleneck_design/mobile_deployment/pytorch/InvBlock/models/imagenet/i2rnet.py a0131fb70c267a9e |
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| Rethinking Bottleneck Structure for Efficient Mobile Network Design |
5 Jul 2020 |
Andrew-Qibin/ssdlite-pytorch/ssd/modeling/backbone/mobilenext.py 778b1206838f15e8 |
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| Angle-based Search Space Shrinking for Neural Architecture Search |
28 Apr 2020 |
megvii-model/AngleNAS/FairNAS/searching/super_model.py a0131fb70c267a9e |
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| Unified Image and Video Saliency Modeling |
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rdroste/unisal/unisal/models/MobileNetV2.py a0131fb70c267a9e |
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| Pixel-in-Pixel Net: Towards Efficient Facial Landmark Detection in the Wild |
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jhb86253817/PIPNet/lib/mobilenetv3.py 4e90491a30c2dc28 |
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| Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference |
3 Jan 2020 |
mit-han-lab/haq-release/models/mobilenetv3.py db82a4013a44fb42 |
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| Fractional Skipping: Towards Finer-Grained Dynamic CNN Inference |
3 Jan 2020 |
mit-han-lab/haq-release/models/mobilenetv2.py bc660f7845db5634 |
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| ZeroQ: A Novel Zero Shot Quantization Framework |
1 Jan 2020 |
jakc4103/DFQ/modeling/classification/MobileNetV2.py a0131fb70c267a9e |
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| GhostNet: More Features from Cheap Operations |
27 Nov 2019 |
ozora-ogino/efficient_backbones/efficient_backbones/efficientnet_v2.py f76badd0c6766f8a |
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| Neural Network Pruning with Residual-Connections and Limited-Data |
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Roll920/CURL/ImageNet/CURL/1_evaluate_filter_importance/mobilenetv2.py a0131fb70c267a9e |
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| SeesawFaceNets: sparse and robust face verification model for mobile platform |
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cvtower/SeesawNet_pytorch/code/models/imagenet/seesaw.py 0db9f814cdec6488 |
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| SqueezeNAS: Fast neural architecture search for faster semantic segmentation |
5 Aug 2019 |
ashaw596/squeezenas/arch/utils.py 2e73e8e10fb7ce2e |
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| EXTD: Extremely Tiny Face Detector via Iterative Filter Reuse |
15 Jun 2019 |
clovaai/EXTD_Pytorch/mobileFacenet_32_PReLU.py 20c32d5668430dcd |
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| Searching for MobileNetV3 |
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wang-zidu/3ddfa-v3/model/mb_v3_networks.py 4e90491a30c2dc28 |
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| Searching for MobileNetV3 |
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chris-boson/fashion_mnist/trainer/models/mobilenetv3.py db82a4013a44fb42 |
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| Towards Efficient Model Compression via Learned Global Ranking |
28 Apr 2019 |
cmu-enyac/LeGR/model/MobileNetV2.py a0131fb70c267a9e |
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| Adaptive Wing Loss for Robust Face Alignment via Heatmap Regression |
16 Apr 2019 |
affromero/SMILE/metrics/mobilenetv2.py a0131fb70c267a9e |
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| SiamRPN++: Evolution of Siamese Visual Tracking with Very Deep Networks |
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STVIR/pysot/pysot/models/backbone/mobile_v2.py a0131fb70c267a9e |
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| OpenPose: Realtime Multi-Person 2D Pose Estimation using Part Affinity Fields |
18 Dec 2018 |
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| ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware |
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| ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware |
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mit-han-lab/haq/models/mobilenetv3.py db82a4013a44fb42 |
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| ProxylessNAS: Direct Neural Architecture Search on Target Task and Hardware |
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mit-han-lab/haq/models/mobilenetv2.py bc660f7845db5634 |
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| TSM: Temporal Shift Module for Efficient Video Understanding |
20 Nov 2018 |
sunutf/TSM/online_demo/mobilenet_v2_tsm.py a0131fb70c267a9e |
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| Unified Perceptual Parsing for Scene Understanding |
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SonpKing/semantic-segmentation-pytorch/models/shufflenetv2.py 7765583b9e540679 |
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| IGCV3: Interleaved Low-Rank Group Convolutions for Efficient Deep Neural Networks |
1 Jun 2018 |
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| MobileNetV2: Inverted Residuals and Linear Bottlenecks |
13 Jan 2018 |
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| Simple Online and Realtime Tracking with a Deep Association Metric |
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levan92/deep_sort_realtime/deep_sort_realtime/embedder/mobilenetv2_bottle.py a0131fb70c267a9e |
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| SSD: Single Shot MultiBox Detector |
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lufficc/SSD/ssd/modeling/backbone/mobilenetv3.py 4e90491a30c2dc28 |
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| FaceNet: A Unified Embedding for Face Recognition and Clustering |
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altndrr/persona/src/models/mobilenet.py db82a4013a44fb42 |
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| arXiv:ijcai2022_0190 |
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OverEuro/deep-head-pose-lite/hopenetlite_v2.py 7765583b9e540679 |
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woshidandan/TANet/code/AVA/train_nni.py c9d11a5f9d03ed48 |
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| arXiv:aaai_6622 |
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| arXiv:aaai_20232 |
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| arXiv:Wang_3D_Face_Reconstruction_with_the_Geometric_Guidance_of_Facial_Part_CVPR_2024_paper |
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| arXiv:Cai_IIEU_Rethinking_Neural_Feature_Activation_from_Decision-Making_ICCV_2023_paper |
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| arXiv:2023.acl-long.803 |
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| arXiv:2023.acl-long.803 |
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