114 citations · 274 across the 5 of their papers we have counts for
9 papers
Refiner: Refining Self-attention for Vision Transformers
Daquan Zhou, Yujun Shi, Bingyi Kang +6
Vision Transformers (ViTs) have shown competitive accuracy in image classification tasks compared with CNNs. Yet, they generally require much more data for model pre-training. Most…
AutoPose: Searching Multi-Scale Branch Aggregation for Pose Estimation
Xinyu Gong, Wuyang Chen, Yifan Jiang +5
We present AutoPose, a novel neural architecture search(NAS) framework that is capable of automatically discovering multiple parallel branches of cross-scale connections towards ac…
AFDet: Anchor Free One Stage 3D Object Detection
Runzhou Ge, Zhuangzhuang Ding, Yihan Hu +4
High-efficiency point cloud 3D object detection operated on embedded systems is important for many robotics applications including autonomous driving. Most previous works try to so…
FNA++: Fast Network Adaptation via Parameter Remapping and Architecture Search
Jiemin Fang, Yuzhu Sun, Qian Zhang +4
Deep neural networks achieve remarkable performance in many computer vision tasks. Most state-of-the-art (SOTA) semantic segmentation and object detection approaches reuse neural n…
FasterSeg: Searching for Faster Real-time Semantic Segmentation
Wuyang Chen, Xinyu Gong, Xianming Liu +3
We present FasterSeg, an automatically designed semantic segmentation network with not only state-of-the-art performance but also faster speed than current methods. Utilizing neura…
Fast Neural Network Adaptation via Parameter Remapping and Architecture Search
Jiemin Fang, Yuzhu Sun, Kangjian Peng +4
Deep neural networks achieve remarkable performance in many computer vision tasks. Most state-of-the-art (SOTA) semantic segmentation and object detection approaches reuse neural n…