activity
20172021
most citedSelf-Monitoring Navigation Agent via Auxiliary Progress Estimation

134 citations · 324 across the 14 of their papers we have counts for

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10 papers · 1 filter

cs.CV2021★ 6 cited

Cross-Domain Adaptive Teacher for Object Detection

Yu-Jhe Li, Xiaoliang Dai, Chih-Yao Ma +6

We address the task of domain adaptation in object detection, where there is a domain gap between a domain with annotations (source) and a domain of interest without annotations (t…

cs.CV2021★ 28 cited

Unbiased Teacher for Semi-Supervised Object Detection

Yen-Cheng Liu, Chih-Yao Ma, Zijian He +6

Semi-supervised learning, i.e., training networks with both labeled and unlabeled data, has made significant progress recently. However, existing works have primarily focused on im…

cs.CV2020★ 9 cited

FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning

Chia-Wen Kuo, Chih-Yao Ma, Jia-Bin Huang +1

Recent state-of-the-art semi-supervised learning (SSL) methods use a combination of image-based transformations and consistency regularization as core components. Such methods, how…

cs.CV2020★ 53 cited

Frustratingly Simple Domain Generalization via Image Stylization

Nathan Somavarapu, Chih-Yao Ma, Zsolt Kira

Convolutional Neural Networks (CNNs) show impressive performance in the standard classification setting where training and testing data are drawn i.i.d. from a given domain. Howeve…

cs.CV2020★ 2 cited

Who2com: Collaborative Perception via Learnable Handshake Communication

Yen-Cheng Liu, Junjiao Tian, Chih-Yao Ma +3

In this paper, we propose the problem of collaborative perception, where robots can combine their local observations with those of neighboring agents in a learnable way to improve…

cs.CV2019★ 1 cited

Learning to Generate Grounded Visual Captions without Localization Supervision

Chih-Yao Ma, Yannis Kalantidis, Ghassan AlRegib +3

When automatically generating a sentence description for an image or video, it often remains unclear how well the generated caption is grounded, that is whether the model uses the…

cs.CV2018★ 16 cited

AdaFrame: Adaptive Frame Selection for Fast Video Recognition

Zuxuan Wu, Caiming Xiong, Chih-Yao Ma +2

We present AdaFrame, a framework that adaptively selects relevant frames on a per-input basis for fast video recognition. AdaFrame contains a Long Short-Term Memory network augment…

cs.CV2017★ 5 cited

Grounded Objects and Interactions for Video Captioning

Chih-Yao Ma, Asim Kadav, Iain Melvin +3

We address the problem of video captioning by grounding language generation on object interactions in the video. Existing work mostly focuses on overall scene understanding with of…

cs.CV2017★ 12 cited

Attend and Interact: Higher-Order Object Interactions for Video Understanding

Chih-Yao Ma, Asim Kadav, Iain Melvin +3

Human actions often involve complex interactions across several inter-related objects in the scene. However, existing approaches to fine-grained video understanding or visual relat…

cs.CV2017★ 39 cited

TS-LSTM and Temporal-Inception: Exploiting Spatiotemporal Dynamics for Activity Recognition

Chih-Yao Ma, Min-Hung Chen, Zsolt Kira +1

Recent two-stream deep Convolutional Neural Networks (ConvNets) have made significant progress in recognizing human actions in videos. Despite their success, methods extending the…