Search Results for author:
Found 9 papers, 2 papers with code
Look, Listen and Recognise: Character-Aware Audio-Visual Subtitling
The goal of this paper is automatic character-aware subtitle generation.
Text-Conditioned Resampler For Long Form Video Understanding
In this paper we present a text-conditioned video resampler (TCR) module that uses a pre-trained and frozen visual encoder and large language model (LLM) to process long video sequences for a task.
Ranked #5 on
Video Question Answering
on NExT-QA
End-to-end Tracking with a Multi-query Transformer
Multiple-object tracking (MOT) is a challenging task that requires simultaneous reasoning about location, appearance, and identity of the objects in the scene over time.
Generalized Few-Shot Video Classification with Video Retrieval and Feature Generation
Few-shot learning aims to recognize novel classes from a few examples.
Video Understanding as Machine Translation
With the advent of large-scale multimodal video datasets, especially sequences with audio or transcribed speech, there has been a growing interest in self-supervised learning of video representations.
Self-Supervised Learning by Cross-Modal Audio-Video Clustering
To the best of our knowledge, XDC is the first self-supervised learning method that outperforms large-scale fully-supervised pretraining for action recognition on the same architecture.
SCSampler: Sampling Salient Clips from Video for Efficient Action Recognition
We demonstrate that the computational cost of action recognition on untrimmed videos can be dramatically reduced by invoking recognition only on these most salient clips.
Ranked #1 on
Action Recognition
on miniSports
Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization
There is a natural correlation between the visual and auditive elements of a video.
Ranked #7 on
Self-Supervised Audio Classification
on ESC-50
Deep-Learning for Classification of Colorectal Polyps on Whole-Slide Images
In this work, we built an automatic image-understanding method that can accurately classify different types of colorectal polyps in whole-slide histology images to help pathologists with histopathological characterization and diagnosis of colorectal polyps.
