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Deformable ConvNets v2: More Deformable, Better Results
Xizhou Zhu, Han Hu, Stephen Lin +1
The superior performance of Deformable Convolutional Networks arises from its ability to adapt to the geometric variations of objects. Through an examination of its adaptive behavi…
Integrated Object Detection and Tracking with Tracklet-Conditioned Detection
Zheng Zhang, Dazhi Cheng, Xizhou Zhu +2
Accurate detection and tracking of objects is vital for effective video understanding. In previous work, the two tasks have been combined in a way that tracking is based heavily on…
Towards High Performance Video Object Detection for Mobiles
Xizhou Zhu, Jifeng Dai, Xingchi Zhu +2
Despite the recent success of video object detection on Desktop GPUs, its architecture is still far too heavy for mobiles. It is also unclear whether the key principles of sparse f…
Learning Region Features for Object Detection
Jiayuan Gu, Han Hu, Liwei Wang +2
While most steps in the modern object detection methods are learnable, the region feature extraction step remains largely hand-crafted, featured by RoI pooling methods. This work p…