38 citations · 43 across the 2 of their papers we have counts for
5 papers
Quantization-Guided Training for Compact TinyML Models
Sedigh Ghamari, Koray Ozcan, Thu Dinh +4
We propose a Quantization Guided Training (QGT) method to guide DNN training towards optimized low-bit-precision targets and reach extreme compression levels below 8-bit precision.…
Counterfactual Visual Explanations
Yash Goyal, Ziyan Wu, Jan Ernst +3
In this work, we develop a technique to produce counterfactual visual explanations. Given a 'query' image for which a vision system predicts class , a counterfactual visual…
Incremental Scene Synthesis
Benjamin Planche, Xuejian Rong, Ziyan Wu +5
We present a method to incrementally generate complete 2D or 3D scenes with the following properties: (a) it is globally consistent at each step according to a learned scene prior,…
Tell Me Where to Look: Guided Attention Inference Network
Kunpeng Li, Ziyan Wu, Kuan-Chuan Peng +2
Weakly supervised learning with only coarse labels can obtain visual explanations of deep neural network such as attention maps by back-propagating gradients. These attention maps…
End-to-end learning of keypoint detector and descriptor for pose invariant 3D matching
Georgios Georgakis, Srikrishna Karanam, Ziyan Wu +2
Finding correspondences between images or 3D scans is at the heart of many computer vision and image retrieval applications and is often enabled by matching local keypoint descript…