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Found 11 papers, 5 papers with code
Wavelet-Guided Acceleration of Text Inversion in Diffusion-Based Image Editing
To address this, we introduce an innovative method that maintains the principles of the NTI while accelerating the image editing process.
HEAR: Hearing Enhanced Audio Response for Video-grounded Dialogue
Video-grounded Dialogue (VGD) aims to answer questions regarding a given multi-modal input comprising video, audio, and dialogue history.
SimPSI: A Simple Strategy to Preserve Spectral Information in Time Series Data Augmentation
Our experimental results support that SimPSI considerably enhances the performance of time series data augmentations by preserving core spectral information.
Neutral Editing Framework for Diffusion-based Video Editing
To this end, this paper proposes Neutral Editing (NeuEdit) framework to enable complex non-rigid editing by changing the motion of a person/object in a video, which has never been attempted before.
SCANet: Scene Complexity Aware Network for Weakly-Supervised Video Moment Retrieval
These proposals are assumed to contain many distinguishable scenes in a video as candidates.
ESD: Expected Squared Difference as a Tuning-Free Trainable Calibration Measure
Studies have shown that modern neural networks tend to be poorly calibrated due to over-confident predictions.
SMSMix: Sense-Maintained Sentence Mixup for Word Sense Disambiguation
To the best of our knowledge, this is the first attempt to apply mixup in NLP while preserving the meaning of a specific word.
Information-Theoretic Text Hallucination Reduction for Video-grounded Dialogue
Despite the recent success of multi-modal reasoning to generate answer sentences, existing dialogue systems still suffer from a text hallucination problem, which denotes indiscriminate text-copying from input texts without an understanding of the question.
Selective Query-guided Debiasing for Video Corpus Moment Retrieval
Video moment retrieval (VMR) aims to localize target moments in untrimmed videos pertinent to a given textual query.
Structured Co-reference Graph Attention for Video-grounded Dialogue
A video-grounded dialogue system referred to as the Structured Co-reference Graph Attention (SCGA) is presented for decoding the answer sequence to a question regarding a given video while keeping track of the dialogue context.
VLANet: Video-Language Alignment Network for Weakly-Supervised Video Moment Retrieval
This paper explores methods for performing VMR in a weakly-supervised manner (wVMR): training is performed without temporal moment labels but only with the text query that describes a segment of the video.
