11 citations · 43 across the 13 of their papers we have counts for
13 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…
Characterizing Video Question Answering with Sparsified Inputs
Shiyuan Huang, Robinson Piramuthu, Vicente Ordonez +2
In Video Question Answering, videos are often processed as a full-length sequence of frames to ensure minimal loss of information. Recent works have demonstrated evidence that spar…
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…
Video in 10 Bits: Few-Bit VideoQA for Efficiency and Privacy
Shiyuan Huang, Robinson Piramuthu, Shih-Fu Chang +1
In Video Question Answering (VideoQA), answering general questions about a video requires its visual information. Yet, video often contains redundant information irrelevant to the…
Towards Fast Adaptation of Pretrained Contrastive Models for Multi-channel Video-Language Retrieval
Xudong Lin, Simran Tiwari, Shiyuan Huang +4
Multi-channel video-language retrieval require models to understand information from different channels (e.g. videoquestion, videospeech) to correctly link a video with a tex…
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…
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…
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…
Flow-Distilled IP Two-Stream Networks for Compressed Video Action Recognition
Shiyuan Huang, Xudong Lin, Svebor Karaman +1
Two-stream networks have achieved great success in video recognition. A two-stream network combines a spatial stream of RGB frames and a temporal stream of Optical Flow to make pre…