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ORDNet: Capturing Omni-Range Dependencies for Scene Parsing
Learning to capture dependencies between spatial positions is essential ...
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Source Data-absent Unsupervised Domain Adaptation through Hypothesis Transfer and Labeling Transfer
Unsupervised domain adaptation (UDA) aims to transfer knowledge from a r...
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Adversarial images for the primate brain
Deep artificial neural networks have been proposed as a model of primate...
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Improving Generalization in Reinforcement Learning with Mixture Regularization
Deep reinforcement learning (RL) agents trained in a limited set of envi...
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Towards Accurate Human Pose Estimation in Videos of Crowded Scenes
Video-based human pose estimation in crowded scenes is a challenging pro...
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Toward Accurate Person-level Action Recognition in Videos of Crowded Scenes
Detecting and recognizing human action in videos with crowded scenes is ...
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A Simple Baseline for Pose Tracking in Videos of Crowded Scenes
This paper presents our solution to ACM MM challenge: Large-scale Human-...
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Towards Theoretically Understanding Why SGD Generalizes Better Than ADAM in Deep Learning
It is not clear yet why ADAM-alike adaptive gradient algorithms suffer f...
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RVL-BERT: Visual Relationship Detection with Visual-Linguistic Knowledge from Pre-trained Representations
Visual relationship detection aims to reason over relationships among sa...
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Dual Adversarial Auto-Encoders for Clustering
As a powerful approach for exploratory data analysis, unsupervised clust...
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ConvBERT: Improving BERT with Span-based Dynamic Convolution
Pre-trained language models like BERT and its variants have recently ach...
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Few-shot Classification via Adaptive Attention
Training a neural network model that can quickly adapt to a new task is ...
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The Devil is in Classification: A Simple Framework for Long-tail Instance Segmentation
Most existing object instance detection and segmentation models only wor...
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Adversarial Self-Supervised Learning for Semi-Supervised 3D Action Recognition
We consider the problem of semi-supervised 3D action recognition which h...
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Combating Domain Shift with Self-Taught Labeling
We present a novel method to combat domain shift when adapting classific...
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Rethinking Bottleneck Structure for Efficient Mobile Network Design
The inverted residual block is dominating architecture design for mobile...
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Local Grid Rendering Networks for 3D Object Detection in Point Clouds
The performance of 3D object detection models over point clouds highly d...
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Inference Stage Optimization for Cross-scenario 3D Human Pose Estimation
Existing 3D human pose estimation models suffer performance drop when ap...
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Overcoming Classifier Imbalance for Long-tail Object Detection with Balanced Group Softmax
Solving long-tail large vocabulary object detection with deep learning b...
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Multi-Miner: Object-Adaptive Region Mining for Weakly-Supervised Semantic Segmentation
Object region mining is a critical step for weakly-supervised semantic s...
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Effective Training Strategies for Deep Graph Neural Networks
Graph Neural Networks (GNNs) tend to suffer performance degradation as m...
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Boosting Few-Shot Learning With Adaptive Margin Loss
Few-shot learning (FSL) has attracted increasing attention in recent yea...
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RAIN: Robust and Accurate Classification Networks with Randomization and Enhancement
Along with the extensive applications of CNN models for classification, ...
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Strip Pooling: Rethinking Spatial Pooling for Scene Parsing
Spatial pooling has been proven highly effective in capturing long-range...
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PANDA: Prototypical Unsupervised Domain Adaptation
Previous adversarial domain alignment methods for unsupervised domain ad...
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A Balanced and Uncertainty-aware Approach for Partial Domain Adaptation
This work addresses the unsupervised domain adaptation problem, especial...
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Cross-layer Feature Pyramid Network for Salient Object Detection
Feature pyramid network (FPN) based models, which fuse the semantics and...
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Do We Really Need to Access the Source Data? Source Hypothesis Transfer for Unsupervised Domain Adaptation
Unsupervised domain adaptation (UDA) aims to leverage the knowledge lear...
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ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning
Recent powerful pre-trained language models have achieved remarkable per...
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The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
We present the findings of "The Alzheimer's Disease Prediction Of Longit...
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MetaSelector: Meta-Learning for Recommendation with User-Level Adaptive Model Selection
Recommender systems often face heterogeneous datasets containing highly ...
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PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection
We propose a single-stage Human-Object Interaction (HOI) detection metho...
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RC-DARTS: Resource Constrained Differentiable Architecture Search
Recent advances show that Neural Architectural Search (NAS) method is ab...
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Zoom in to where it matters: a hierarchical graph based model for mammogram analysis
In clinical practice, human radiologists actually review medical images ...
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Efficient Differentiable Neural Architecture Search with Meta Kernels
The searching procedure of neural architecture search (NAS) is notorious...
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Classification Calibration for Long-tail Instance Segmentation
Remarkable progress has been made in object instance detection and segme...
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Decoupling Representation and Classifier for Long-Tailed Recognition
The long-tail distribution of the visual world poses great challenges fo...
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On Robustness of Neural Ordinary Differential Equations
Neural ordinary differential equations (ODEs) have been attracting incre...
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Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
In this paper, we aim to tackle the task of semi-supervised video object...
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Revisit Knowledge Distillation: a Teacher-free Framework
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersom...
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Hierarchic Neighbors Embedding
Manifold learning now plays a very important role in machine learning an...
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PSGAN: Pose-Robust Spatial-Aware GAN for Customizable Makeup Transfer
We propose a novel Pose-robust Spatial-aware GAN (PSGAN) for transferrin...
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Single-Stage Multi-Person Pose Machines
Multi-person pose estimation is a challenging problem. Existing methods ...
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Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
Existing video-based human pose estimation methods extensively apply lar...
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PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
Despite the great progress made by deep CNNs in image semantic segmentat...
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Central Similarity Hashing via Hadamard matrix
Hashing has been widely used for efficient large-scale multimedia data r...
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Deep Model Compression via Filter Auto-sampling
The recent WSNet [1] is a new model compression method through sampling ...
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Delving into 3D Action Anticipation from Streaming Videos
Action anticipation, which aims to recognize the action with a partial o...
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VRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
Human motion prediction, which aims to predict future human poses given ...
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Unsupervised Image Noise Modeling with Self-Consistent GAN
Noise modeling lies in the heart of many image processing tasks. However...
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