107 citations · 162 across the 15 of their papers we have counts for
15 papers
WIDIn: Wording Image for Domain-Invariant Representation in Single-Source Domain Generalization
Jiawei Ma, Yulei Niu, Shiyuan Huang +2
Language has been useful in extending the vision encoder to data from diverse distributions without empirical discovery in training domains. However, as the image description is mo…
Hybrid-SORT: Weak Cues Matter for Online Multi-Object Tracking
Mingzhan Yang, Guangxin Han, Bin Yan +4
Multi-Object Tracking (MOT) aims to detect and associate all desired objects across frames. Most methods accomplish the task by explicitly or implicitly leveraging strong cues (i.e…
Supervised Masked Knowledge Distillation for Few-Shot Transformers
Han Lin, Guangxing Han, Jiawei Ma +3
Vision Transformers (ViTs) emerge to achieve impressive performance on many data-abundant computer vision tasks by capturing long-range dependencies among local features. However,…
DiGeo: Discriminative Geometry-Aware Learning for Generalized Few-Shot Object Detection
Jiawei Ma, Yulei Niu, Jincheng Xu +3
Generalized few-shot object detection aims to achieve precise detection on both base classes with abundant annotations and novel classes with limited training data. Existing approa…
TempCLR: Temporal Alignment Representation with Contrastive Learning
Yuncong Yang, Jiawei Ma, Shiyuan Huang +4
Video representation learning has been successful in video-text pre-training for zero-shot transfer, where each sentence is trained to be close to the paired video clips in a commo…
Weakly-Supervised Temporal Article Grounding
Long Chen, Yulei Niu, Brian Chen +6
Given a long untrimmed video and natural language queries, video grounding (VG) aims to temporally localize the semantically-aligned video segments. Almost all existing VG work hol…
Explicit Image Caption Editing
Zhen Wang, Long Chen, Wenbo Ma +4
Given an image and a reference caption, the image caption editing task aims to correct the misalignment errors and generate a refined caption. However, all existing caption editing…
Multi-Modal Few-Shot Object Detection with Meta-Learning-Based Cross-Modal Prompting
Guangxing Han, Long Chen, Jiawei Ma +3
We study multi-modal few-shot object detection (FSOD) in this paper, using both few-shot visual examples and class semantic information for detection, which are complementary to ea…
Few-Shot Object Detection with Fully Cross-Transformer
Guangxing Han, Jiawei Ma, Shiyuan Huang +2
Few-shot object detection (FSOD), with the aim to detect novel objects using very few training examples, has recently attracted great research interest in the community. Metric-lea…
The Met Dataset: Instance-level Recognition for Artworks
Nikolaos-Antonios Ypsilantis, Noa Garcia, Guangxing Han +3
This work introduces a dataset for large-scale instance-level recognition in the domain of artworks. The proposed benchmark exhibits a number of different challenges such as large…
Query Adaptive Few-Shot Object Detection with Heterogeneous Graph Convolutional Networks
Guangxing Han, Yicheng He, Shiyuan Huang +2
Few-shot object detection (FSOD) aims to detect never-seen objects using few examples. This field sees recent improvement owing to the meta-learning techniques by learning how to m…
Partner-Assisted Learning for Few-Shot Image Classification
Jiawei Ma, Hanchen Xie, Guangxing Han +3
Few-shot Learning has been studied to mimic human visual capabilities and learn effective models without the need of exhaustive human annotation. Even though the idea of meta-learn…
Meta Faster R-CNN: Towards Accurate Few-Shot Object Detection with Attentive Feature Alignment
Guangxing Han, Shiyuan Huang, Jiawei Ma +2
Few-shot object detection (FSOD) aims to detect objects using only a few examples. How to adapt state-of-the-art object detectors to the few-shot domain remains challenging. Object…
Task-Adaptive Negative Envision for Few-Shot Open-Set Recognition
Shiyuan Huang, Jiawei Ma, Guangxing Han +1
We study the problem of few-shot open-set recognition (FSOR), which learns a recognition system capable of both fast adaptation to new classes with limited labeled examples and rej…
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
Qingyun Wang, Manling Li, Xuan Wang +24
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and rel…