Search Results for author:
Found 7 papers, 5 papers with code
OW-DETR: Open-world Detection Transformer
In the case of incremental object detection, OW-DETR outperforms the state-of-the-art for all settings on PASCAL VOC.
Discriminative Region-based Multi-Label Zero-Shot Learning
We note that the best existing multi-label ZSL method takes a shared approach towards attending to region features with a common set of attention maps for all the classes.
Ranked #1 on
Multi-label zero-shot learning
on Open Images V4
Generative Multi-Label Zero-Shot Learning
Nevertheless, computing reliable attention maps for unseen classes during inference in a multi-label setting is still a challenge.
Ranked #4 on
Multi-label zero-shot learning
on NUS-WIDE
Safety Verification of Model Based Reinforcement Learning Controllers
The proposed frame-work can efficiently handle models and controllers which are represented using neural networks.
Safety-guaranteed Reinforcement Learning based on Multi-class Support Vector Machine
The proposed algorithm is developed for the discrete state and action space and utilizes a multi-class support vector machine (SVM) to represent the policy.
Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification
We propose to enforce semantic consistency at all stages of (generalized) zero-shot learning: training, feature synthesis and classification.
Ranked #1 on
Zero-Shot Learning
on SUN Attribute
iSAID: A Large-scale Dataset for Instance Segmentation in Aerial Images
Compared to existing small-scale aerial image based instance segmentation datasets, iSAID contains 15$\times$ the number of object categories and 5$\times$ the number of instances.
Ranked #1 on
Object Detection
on iSAID
