342 citations · 2.4k across the 71 of their papers we have counts for
12 papers · 1 filter
Are Fewer Labels Possible for Few-shot Learning?
Suichan Li, Dongdong Chen, Yinpeng Chen +4
Few-shot learning is challenging due to its very limited data and labels. Recent studies in big transfer (BiT) show that few-shot learning can greatly benefit from pretraining on l…
Efficient Semantic Image Synthesis via Class-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +6
Spatially-adaptive normalization (SPADE) is remarkably successful recently in conditional semantic image synthesis \cite{park2019semantic}, which modulates the normalized activatio…
Unsupervised Pre-training for Person Re-identification
Dengpan Fu, Dongdong Chen, Jianmin Bao +5
In this paper, we present a large scale unlabeled person re-identification (Re-ID) dataset "LUPerson" and make the first attempt of performing unsupervised pre-training for improvi…
MicroNet: Towards Image Recognition with Extremely Low FLOPs
Yunsheng Li, Yinpeng Chen, Xiyang Dai +6
In this paper, we present MicroNet, which is an efficient convolutional neural network using extremely low computational cost (e.g. 6 MFLOPs on ImageNet classification). Such a low…
MichiGAN: Multi-Input-Conditioned Hair Image Generation for Portrait Editing
Zhentao Tan, Menglei Chai, Dongdong Chen +5
Despite the recent success of face image generation with GANs, conditional hair editing remains challenging due to the under-explored complexity of its geometry and appearance. In…
GreedyFool: Distortion-Aware Sparse Adversarial Attack
Xiaoyi Dong, Dongdong Chen, Jianmin Bao +5
Modern deep neural networks(DNNs) are vulnerable to adversarial samples. Sparse adversarial samples are a special branch of adversarial samples that can fool the target model by on…
LSM: Learning Subspace Minimization for Low-level Vision
Chengzhou Tang, Lu Yuan, Ping Tan
We study the energy minimization problem in low-level vision tasks from a novel perspective. We replace the heuristic regularization term with a learnable subspace constraint, and…
Cross-domain Correspondence Learning for Exemplar-based Image Translation
Pan Zhang, Bo Zhang, Dong Chen +2
We present a general framework for exemplar-based image translation, which synthesizes a photo-realistic image from the input in a distinct domain (e.g., semantic segmentation mask…
Rethinking Spatially-Adaptive Normalization
Zhentao Tan, Dongdong Chen, Qi Chu +5
Spatially-adaptive normalization is remarkably successful recently in conditional semantic image synthesis, which modulates the normalized activation with spatially-varying transfo…
Density-Aware Graph for Deep Semi-Supervised Visual Recognition
Suichan Li, Bin Liu, Dongdong Chen +3
Semi-supervised learning (SSL) has been extensively studied to improve the generalization ability of deep neural networks for visual recognition. To involve the unlabelled data, mo…
DA-NAS: Data Adapted Pruning for Efficient Neural Architecture Search
Xiyang Dai, Dongdong Chen, Mengchen Liu +2
Efficient search is a core issue in Neural Architecture Search (NAS). It is difficult for conventional NAS algorithms to directly search the architectures on large-scale tasks like…
Dynamic ReLU
Yinpeng Chen, Xiyang Dai, Mengchen Liu +3
Rectified linear units (ReLU) are commonly used in deep neural networks. So far ReLU and its generalizations (non-parametric or parametric) are static, performing identically for a…