Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval
The increasing prevalence of video clips has sparked growing interest in text-video retrieval.
Recent advances focus on establishing a joint embedding space for text and video relying …
Recent advances focus on establishing a joint embedding space for text and video relying …
Ranking Distillation for Open-Ended Video Question Answering with Insufficient Labels
This paper focuses on open-ended video question answering which aims to find the correct
answers from a large answer set in response to a video-related question. This is essentially …
answers from a large answer set in response to a video-related question. This is essentially …
Text-Video Retrieval via Multi-Modal Hypergraph Networks
Text-video retrieval is a challenging task that aims to identify relevant videos given textual
queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval …
queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval …
SIA-Net: Sparse Interactive Attention Network for Multimodal Emotion Recognition
S Li, T Zhang, CLP Chen - IEEE Transactions on Computational …, 2024 - ieeexplore.ieee.org
Multimodal emotion recognition (MER) integrates multiple modalities to identify the user's
emotional state, which is the core technology of natural and friendly human–computer …
emotional state, which is the core technology of natural and friendly human–computer …
EA-VTR: Event-Aware Video-Text Retrieval
Understanding the content of events occurring in the video and their inherent temporal logic
is crucial for video-text retrieval. However, web-crawled pre-training datasets often lack …
is crucial for video-text retrieval. However, web-crawled pre-training datasets often lack …
A new multi-picture architecture for learned video deinterlacing and demosaicing with parallel deformable convolution and self-attention blocks
Despite the fact real-world video deinterlacing and demosaicing are well-suited to
supervised learning from synthetically degraded data because the degradation models are …
supervised learning from synthetically degraded data because the degradation models are …
Text-Video Retrieval via Variational Multi-Modal Hypergraph Networks
Text-video retrieval is a challenging task that aims to identify relevant videos given textual
queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval …
queries. Compared to conventional textual retrieval, the main obstacle for text-video retrieval …
Multi-Modal Inductive Framework for Text-Video Retrieval
Text-video retrieval (TVR) identifies relevant videos based on textual queries. Existing
methods are limited by their ability to understand and connect different modalities, resulting …
methods are limited by their ability to understand and connect different modalities, resulting …
SViTT-Ego: A Sparse Video-Text Transformer for Egocentric Video
Pretraining egocentric vision-language models has become essential to improving
downstream egocentric video-text tasks. These egocentric foundation models commonly use …
downstream egocentric video-text tasks. These egocentric foundation models commonly use …
[PDF][PDF] Supplementary Material of “Text Is MASS: Modeling as Stochastic Embedding for Text-Video Retrieval”
We provide more results, visualizations, and in-depth discussions of the proposed T-MASS
as follows• More quantitative performance of T-MASS (Section 1).• Discussions about …
as follows• More quantitative performance of T-MASS (Section 1).• Discussions about …