15 citations · 44 across the 7 of their papers we have counts for
17 papers · 1 filter
Everybody Tracking Every Body
Daeyun Shin, Yunhan Zhao, Shu Kong +2
We address the problem of 3D body pose estimation of multiple interacting people from their egocentric views with centralized coordination. Each individual wears a camera recording…
Improving Knowledge Distillation via Regularizing Feature Norm and Direction
Yuzhu Wang, Lechao Cheng, Manni Duan +3
Knowledge distillation (KD) exploits a large well-trained model (i.e., teacher) to train a small student model on the same dataset for the same task. Treating teacher features as k…
Far3Det: Towards Far-Field 3D Detection
Shubham Gupta, Jeet Kanjani, Mengtian Li +4
We focus on the task of far-field 3D detection (Far3Det) of objects beyond a certain distance from an observer, e.g., 50m. Far3Det is particularly important for autonomous vehic…
Long-Tailed Recognition via Weight Balancing
Shaden Alshammari, Yu-Xiong Wang, Deva Ramanan +1
In the real open world, data tends to follow long-tailed class distributions, motivating the well-studied long-tailed recognition (LTR) problem. Naive training produces models that…
OpenGAN: Open-Set Recognition via Open Data Generation
Shu Kong, Deva Ramanan
Real-world machine learning systems need to analyze test data that may differ from training data. In K-way classification, this is crisply formulated as open-set recognition, core…
Camera Pose Matters: Improving Depth Prediction by Mitigating Pose Distribution Bias
Yunhan Zhao, Shu Kong, Charless Fowlkes
Monocular depth predictors are typically trained on large-scale training sets which are naturally biased w.r.t the distribution of camera poses. As a result, trained predictors fai…