PA&DA: Jointly Sampling PAth and DAta for Consistent NAS |
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Top-Down Visual Attention from Analysis by Synthesis |
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CUF: Continuous Upsampling Filters |
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Curvature-Balanced Feature Manifold Learning for Long-tailed Classification |
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Neighborhood Attention Transformer |
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Progressive Random Convolutions for Single Domain Generalization |
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Domain Expansion of Image Generators |
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Gradient Norm Aware Minimization Seeks First-Order Flatness and Improves Generalization |
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Boosting Verified Training for Robust Image Classifications via Abstraction |
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Joint Token Pruning and Squeezing Towards more Aggressive Compression of Vision Transformers |
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PointListNet: Deep Learning on 3D Point Lists |
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Rate Gradient Approximation Attack Threats Deep Spiking Neural Networks |
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Masked Jigsaw Puzzle: A Versatile Position Embedding for Vision Transformers |
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Deep Graph Reprogramming |
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ConvNeXt V2: Co-Designing and Scaling ConvNets with Masked Autoencoders |
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Frustratingly Easy Regularization on Representation can Boost Deep Reinforcement Learning |
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Unified Pose Sequence Modeling |
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RIFormer: Keep Your Vision Backbone Effective but Removing Token Mixer |
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Real-Time Neural Light Field on Mobile Devices |
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Towards Scalable Neural Representation for Diverse Videos |
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AutoFocusFormer: Image Segmentation Off the Grid |
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Minimizing the Accumulated Trajectory Error to Improve Dataset Distillation |
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Deep Learning of Partial Graph Matching via Differentiable Top-K |
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WIRE: Wavelet Implicit Neural Representations |
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Decompose, Adjust, Compose: Effective Normalization by Playing with Frequency for Domain Generalization |
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Towards a Smaller Student: Capacity Dynamic Distillation for Efficient Image Retrieval |
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UniHCP: A Unified Model for Human-Centric Perceptions |
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Trainable Projected Gradient Method for Robust Fine-Tuning |
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Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data |
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B-Spline Texture Coefficients Estimator for Screen Content Image Super-Resolution |
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Run, Don't Walk: Chasing Higher FLOPS for Faster Neural Networks |
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HyperMatch: Noise-Tolerant Semi-Supervised Learning via Relaxed Contrastive Constraint |
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From Node Interaction to Hop Interaction: New Effective and Scalable Graph Learning Paradigm |
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Slide-Transformer: Hierarchical Vision Transformer with Local Self-Attention |
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On the Pitfall of Mixup for Uncertainty Calibration |
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Edges to Shapes to Concepts: Adversarial Augmentation for Robust Vision |
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Mod-Squad: Designing Mixtures of Experts as Modular Multi-Task Learners |
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DeepMAD: Mathematical Architecture Design for Deep Convolutional Neural Network |
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PaCa-ViT: Learning Patch-to-Cluster Attention in Vision Transformers |
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BiFormer: Vision Transformer with Bi-Level Routing Attention |
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DeSTSeg: Segmentation Guided Denoising Student-Teacher for Anomaly Detection |
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Hierarchical Neural Memory Network for Low Latency Event Processing |
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Block Selection Method for using Feature Norm in Out-of-Distribution Detection |
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NAR-Former: Neural Architecture Representation Learning Towards Holistic Attributes Prediction |
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MDL-NAS: A Joint Multi-Domain Learning Framework for Vision Transformer |
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VNE: An Effective Method for Improving Deep Representation by Manipulating Eigenvalue Distribution |
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Multi-Agent Automated Machine Learning |
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Making Vision Transformers Efficient from a Token Sparsification View |
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Integral Neural Networks |
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RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving |
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MIANet: Aggregating Unbiased Instance and General Information for Few-Shot Semantic Segmentation |
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One-Shot Model for Mixed-Precision Quantization |
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Learning Dynamic Style Kernels for Artistic Style Transfer |
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SVGformer: Representation Learning for Continuous Vector Graphics using Transformers |
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How to Prevent the Continuous Damage of Noises to Model Training? |
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GKEAL: Gaussian Kernel Embedded Analytic Learning for Few-Shot Class Incremental Task |
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Differentiable Architecture Search with Random Features |
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ERM-KTP: Knowledge-Level Machine Unlearning via Knowledge Transfer |
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FIANCEE: Faster Inference of Adversarial Networks via Conditional Early Exits |
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Beyond Attentive Tokens: Incorporating Token Importance and Diversity for Efficient Vision Transformers |
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Token Turing Machines |
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Co-Training 2L Submodels for Visual Recognition |
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HOTNAS: Hierarchical Optimal Transport for Neural Architecture Search |
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SLACK: Stable Learning of Augmentations with Cold-Start and KL Regularization |
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MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins |
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Alias-Free Convnets: Fractional Shift Invariance via Polynomial Activations |
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Detection of Out-of-Distribution Samples using Binary Neuron Activation Patterns |
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Mitigating Task Interference in Multi-Task Learning via Explicit Task Routing with Non-Learnable Primitives |
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Superclass Learning with Representation Enhancement |
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Perception and Semantic Aware Regularization for Sequential Confidence Calibration |
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DART: Diversify-Aggregate-Repeat Training Improves Generalization of Neural Networks |
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Improving Robustness of Vision Transformers by Reducing Sensitivity to Patch Corruptions |
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E2PN: Efficient SE(3)-Equivariant Point Network |
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Generalization Matters: Loss Minima Flattening via Parameter Hybridization for Efficient Online Knowledge Distillation |
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Regularization of Polynomial Networks for Image Recognition |
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Hyperspherical Embedding for Point Cloud Completion |
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On the Effectiveness of Partial Variance Reduction in Federated Learning with Heterogeneous Data |
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Independent Component Alignment for Multi-Task Learning |
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MP-Former: Mask-Piloted Transformer for Image Segmentation |
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SMPConv: Self-Moving Point Representations for Continuous Convolution |
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MaskCon: Masked Contrastive Learning for Coarse-Labelled Dataset |
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FlexiViT: One Model for All Patch Sizes |
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GEN: Pushing the Limits of Softmax-based Out-of-Distribution Detection |
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Zero-Shot Noise2Noise: Efficient Image Denoising without Any Data |
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Castling-ViT: Compressing Self-Attention via Switching Towards Linear-Angular Attention at Vision Transformer Inference |
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HNeRV: A Hybrid Neural Representation for Videos |
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Re-Basin via Implicit Sinkhorn Differentiation |
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Bayesian Posterior Approximation with Stochastic Ensembles |
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FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning |
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Enhancing Multiple Reliability Measures via Nuisance-Extended Information Bottleneck |
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Federated Learning with Data-Agnostic Distribution Fusion |
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