Publications
Frustratingly Simple Few-Shot Object Detection
ICML 2020 State-of-the-art few-shot detection method with backpropagation learning.
Learning Saliency Propagation for Semi-Supervised Instance Segmentation
CVPR 2020 We propose a ShapeProp module to propagate information between object detection and segmentation supervisions for Semi-Supervised Instance Segmentation.
Joint Monocular 3D Vehicle Detection and Tracking
ICCV 2019 We propose a novel online framework for 3D vehicle detection and tracking from monocular videos.
Disentangling Propagation and Generation for Video Prediction
ICCV 2019 We describe a computational model for high-fidelity video prediction which disentangles motion-specific propagation from motion-agnostic generation.
Few Shot Object Detection via Feature Reweighting
ICCV 2019 We develop a few-shot object detector that can learn to detect novel objects from only a few annotated examples.
Deep Mixture of Experts via Shallow Embedding
UAI 2019 We explore a mixture of experts (MoE) approach to deep dynamic routing, which activates certain experts in the network on a per-example basis.
TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning
CVPR 2019 We propose Task-Aware Feature Embedding Networks (TAFE-Nets) to learn how to adapt the image representation to a new task in a meta learning fashion.
Hierarchical Discrete Distribution Decomposition for Match Density Estimation
CVPR 2019 We propose Hierarchical Discrete Distribution Decomposition (HD^3), a framework suitable for learning probabilistic pixel correspondences in both optical flow and stereo matching.
Semantic Predictive Control for Explainable and Efficient Policy Learning
ICRA 2019 We propose a driving policy learning framework that predicts feature representations of future visual inputs.