619 citations · 6.4k across the 178 of their papers we have counts for
41 papers · 1 filter
RC-DARTS: Resource Constrained Differentiable Architecture Search
Xiaojie Jin, Jiang Wang, Joshua Slocum +4
Recent advances show that Neural Architectural Search (NAS) method is able to find state-of-the-art image classification deep architectures. In this paper, we consider the one-shot…
Zoom in to where it matters: a hierarchical graph based model for mammogram analysis
Hao Du, Jiashi Feng, Mengling Feng
In clinical practice, human radiologists actually review medical images with high resolution monitors and zoom into region of interests (ROIs) for a close-up examination. Inspired…
Efficient Differentiable Neural Architecture Search with Meta Kernels
Shoufa Chen, Yunpeng Chen, Shuicheng Yan +1
The searching procedure of neural architecture search (NAS) is notoriously time consuming and cost prohibitive.To make the search space continuous, most existing gradient-based NAS…
PPDM: Parallel Point Detection and Matching for Real-time Human-Object Interaction Detection
Yue Liao, Si Liu, Fei Wang +3
We propose a single-stage Human-Object Interaction (HOI) detection method that has outperformed all existing methods on HICO-DET dataset at 37 fps on a single Titan XP GPU. It is t…
Compressed Video Action Recognition with Refined Motion Vector
Haoyuan Cao, Shining Yu, Jiashi Feng
Although CNN has reached satisfactory performance in image-related tasks, using CNN to process videos is much more challenging due to the enormous size of raw video streams. In thi…
Classification Calibration for Long-tail Instance Segmentation
Tao Wang, Yu Li, Bingyi Kang +5
Remarkable progress has been made in object instance detection and segmentation in recent years. However, existing state-of-the-art methods are mostly evaluated with fairly balance…
Decoupling Representation and Classifier for Long-Tailed Recognition
Bingyi Kang, Saining Xie, Marcus Rohrbach +4
The long-tail distribution of the visual world poses great challenges for deep learning based classification models on how to handle the class imbalance problem. Existing solutions…
On Robustness of Neural Ordinary Differential Equations
Hanshu Yan, Jiawei Du, Vincent Y. F. Tan +1
Neural ordinary differential equations (ODEs) have been attracting increasing attention in various research domains recently. There have been some works studying optimization issue…
Adaptive ROI Generation for Video Object Segmentation Using Reinforcement Learning
Mingjie Sun, Jimin Xiao, Eng Gee Lim +2
In this paper, we aim to tackle the task of semi-supervised video object segmentation across a sequence of frames where only the ground-truth segmentation of the first frame is pro…
Hierarchic Neighbors Embedding
Shenglan Liu, Yang Yu, Yang Liu +3
Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution,…
Revisiting Knowledge Distillation via Label Smoothing Regularization
Li Yuan, Francis E. H. Tay, Guilin Li +2
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersome teacher model into a lightweight student model. Its success is generally attributed to the privileged info…
PSGAN: Pose and Expression Robust Spatial-Aware GAN for Customizable Makeup Transfer
Wentao Jiang, Si Liu, Chen Gao +4
In this paper, we address the makeup transfer task, which aims to transfer the makeup from a reference image to a source image. Existing methods have achieved promising progress in…
Single-Stage Multi-Person Pose Machines
Xuecheng Nie, Jianfeng Zhang, Shuicheng Yan +1
Multi-person pose estimation is a challenging problem. Existing methods are mostly two-stage based--one stage for proposal generation and the other for allocating poses to correspo…
Dynamic Kernel Distillation for Efficient Pose Estimation in Videos
Xuecheng Nie, Yuncheng Li, Linjie Luo +2
Existing video-based human pose estimation methods extensively apply large networks onto every frame in the video to localize body joints, which suffer high computational cost and…
PANet: Few-Shot Image Semantic Segmentation with Prototype Alignment
Kaixin Wang, Jun Hao Liew, Yingtian Zou +2
Despite the great progress made by deep CNNs in image semantic segmentation, they typically require a large number of densely-annotated images for training and are difficult to gen…
Central Similarity Quantization for Efficient Image and Video Retrieval
Li Yuan, Tao Wang, Xiaopeng Zhang +4
Existing data-dependent hashing methods usually learn hash functions from pairwise or triplet data relationships, which only capture the data similarity locally, and often suffer f…
Neural Epitome Search for Architecture-Agnostic Network Compression
Daquan Zhou, Xiaojie Jin, Qibin Hou +3
The recent WSNet [1] is a new model compression method through sampling filterweights from a compact set and has demonstrated to be effective for 1D convolutionneural networks (CNN…
Distilling Object Detectors with Fine-grained Feature Imitation
Tao Wang, Li Yuan, Xiaopeng Zhang +1
State-of-the-art CNN based recognition models are often computationally prohibitive to deploy on low-end devices. A promising high level approach tackling this limitation is knowle…
Understanding Adversarial Behavior of DNNs by Disentangling Non-Robust and Robust Components in Performance Metric
Yujun Shi, Benben Liao, Guangyong Chen +3
The vulnerability to slight input perturbations is a worrying yet intriguing property of deep neural networks (DNNs). Despite many previous works studying the reason behind such ad…
Deep Face Recognition Model Compression via Knowledge Transfer and Distillation
Jayashree Karlekar, Jiashi Feng, Zi Sian Wong +1
Fully convolutional networks (FCNs) have become de facto tool to achieve very high-level performance for many vision and non-vision tasks in general and face recognition in particu…
Panoptic Edge Detection
Yuan Hu, Yingtian Zou, Jiashi Feng
Pursuing more complete and coherent scene understanding towards realistic vision applications drives edge detection from category-agnostic to category-aware semantic level. However…
Delving into 3D Action Anticipation from Streaming Videos
Hongsong Wang, Jiashi Feng
Action anticipation, which aims to recognize the action with a partial observation, becomes increasingly popular due to a wide range of applications. In this paper, we investigate…
PVRED: A Position-Velocity Recurrent Encoder-Decoder for Human Motion Prediction
Hongsong Wang, Jian Dong, Bin Cheng +1
Human motion prediction, which aims to predict future human poses given past poses, has recently seen increased interest. Many recent approaches are based on Recurrent Neural Netwo…
Unsupervised Image Noise Modeling with Self-Consistent GAN
Hanshu Yan, Xuan Chen, Vincent Y. F. Tan +3
Noise modeling lies in the heart of many image processing tasks. However, existing deep learning methods for noise modeling generally require clean and noisy image pairs for model…