research
∙
03/25/2023
Supervised Masked Knowledge Distillation for Few-Shot Transformers
Vision Transformers (ViTs) emerge to achieve impressive performance on m...
share
research
∙
03/16/2023
DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detection
Generalized few-shot object detection aims to achieve precise detection ...
research
∙
10/15/2022
Video in 10 Bits: Few-Bit VideoQA for Efficiency and Privacy
In Video Question Answering (VideoQA), answering general questions about...
research
∙
06/05/2022
Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval
Multi-channel video-language retrieval require models to understand info...
research
∙
04/16/2022
Multimodal Few-Shot Object Detection with Meta-Learning Based Cross-Modal Prompting
We study multimodal few-shot object detection (FSOD) in this paper, usin...
research
∙
03/28/2022
Few-Shot Object Detection with Fully Cross-Transformer
Few-shot object detection (FSOD), with the aim to detect novel objects u...
research
∙
12/17/2021
Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks
Few-shot object detection (FSOD) aims to detect never-seen objects using...
research
∙
04/15/2021
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
Few-shot object detection (FSOD) aims to detect objects using only few e...
research
∙
12/24/2020
Task-Adaptive Negative Class Envision for Few-Shot Open-Set Recognition
Recent works seek to endow recognition systems with the ability to handl...
research
∙
12/10/2019
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition
Two-stream networks have achieved great success in video recognition. A ...
research
∙
12/10/2019