8 citations · 19 across the 15 of their papers we have counts for
15 papers
OSCaR: Object State Captioning and State Change Representation
Nguyen Nguyen, Jing Bi, Ali Vosoughi +3
The capability of intelligent models to extrapolate and comprehend changes in object states is a crucial yet demanding aspect of AI research, particularly through the lens of human…
Adaptive Super Resolution For One-Shot Talking-Head Generation
Luchuan Song, Pinxin Liu, Guojun Yin +1
The one-shot talking-head generation learns to synthesize a talking-head video with one source portrait image under the driving of same or different identity video. Usually these m…
Discover and Mitigate Multiple Biased Subgroups in Image Classifiers
Zeliang Zhang, Mingqian Feng, Zhiheng Li +1
Machine learning models can perform well on in-distribution data but often fail on biased subgroups that are underrepresented in the training data, hindering the robustness of mode…
Approximated Likelihood Ratio: A Forward-Only and Parallel Framework for Boosting Neural Network Training
Zeliang Zhang, Jinyang Jiang, Zhuo Liu +3
Efficient and biologically plausible alternatives to backpropagation in neural network training remain a challenge due to issues such as high computational complexity and additiona…
Efficiently Leveraging Linguistic Priors for Scene Text Spotting
Nguyen Nguyen, Yapeng Tian, Chenliang Xu
Incorporating linguistic knowledge can improve scene text recognition, but it is questionable whether the same holds for scene text spotting, which typically involves text detectio…
Learning Audio Concepts from Counterfactual Natural Language
Ali Vosoughi, Luca Bondi, Ho-Hsiang Wu +1
Conventional audio classification relied on predefined classes, lacking the ability to learn from free-form text. Recent methods unlock learning joint audio-text embeddings from ra…