143 citations · 418 across the 21 of their papers we have counts for
6 papers · 1 filter
Part-Guided Attention Learning for Vehicle Instance Retrieval
Xinyu Zhang, Rufeng Zhang, Jiewei Cao +3
Vehicle instance retrieval often requires one to recognize the fine-grained visual differences between vehicles. Besides the holistic appearance of vehicles which is easily affecte…
Regularizing Proxies with Multi-Adversarial Training for Unsupervised Domain-Adaptive Semantic Segmentation
Tong Shen, Dong Gong, Wei Zhang +2
Training a semantic segmentation model requires a large amount of pixel-level annotation, hampering its application at scale. With computer graphics, we can generate almost unlimit…
RGBD Based Dimensional Decomposition Residual Network for 3D Semantic Scene Completion
Jie Li, Yu Liu, Dong Gong +4
RGB images differentiate from depth images as they carry more details about the color and texture information, which can be utilized as a vital complementary to depth for boosting…
Attention-guided Network for Ghost-free High Dynamic Range Imaging
Qingsen Yan, Dong Gong, Qinfeng Shi +4
Ghosting artifacts caused by moving objects or misalignments is a key challenge in high dynamic range (HDR) imaging for dynamic scenes. Previous methods first register the input lo…
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection
Dong Gong, Lingqiao Liu, Vuong Le +4
Deep autoencoder has been extensively used for anomaly detection. Training on the normal data, the autoencoder is expected to produce higher reconstruction error for the abnormal i…
Knowledge Adaptation for Efficient Semantic Segmentation
Tong He, Chunhua Shen, Zhi Tian +3
Both accuracy and efficiency are of significant importance to the task of semantic segmentation. Existing deep FCNs suffer from heavy computations due to a series of high-resolutio…