2 citations · 5 across the 5 of their papers we have counts for
4 papers · 1 filter
Proposal Distribution Calibration for Few-Shot Object Detection
Bohao Li, Chang Liu, Mengnan Shi +3
Adapting object detectors learned with sufficient supervision to novel classes under low data regimes is charming yet challenging. In few-shot object detection (FSOD), the two-step…
Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers
Yunjie Tian, Lingxi Xie, Jiemin Fang +6
The past year has witnessed a rapid development of masked image modeling (MIM). MIM is mostly built upon the vision transformers, which suggests that self-supervised visual represe…
Self-supervised Feature-Gate Coupling for Dynamic Network Pruning
Mengnan Shi, Chang Liu, Jianbin Jiao +1
Gating modules have been widely explored in dynamic network pruning to reduce the run-time computational cost of deep neural networks while preserving the representation of feature…
A scalable convolutional neural network for task-specified scenarios via knowledge distillation
Mengnan Shi, Fei Qin, Qixiang Ye +2
In this paper, we explore the redundancy in convolutional neural network, which scales with the complexity of vision tasks. Considering that many front-end visual systems are inter…