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Found 11 papers, 7 papers with code
Reka Core, Flash, and Edge: A Series of Powerful Multimodal Language Models
On text benchmarks, Core not only performs competitively to other frontier models on a set of well-established benchmarks (e. g. MMLU, GSM8K) but also outperforms GPT4-0613 on human evaluation.
AutoAD II: The Sequel -- Who, When, and What in Movie Audio Description
Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences.
OxfordVGG Submission to the EGO4D AV Transcription Challenge
This report presents the technical details of our submission on the EGO4D Audio-Visual (AV) Automatic Speech Recognition Challenge 2023 from the OxfordVGG team.
Balancing the Picture: Debiasing Vision-Language Datasets with Synthetic Contrast Sets
To address this issue, we propose a novel dataset debiasing pipeline to augment the COCO dataset with synthetic, gender-balanced contrast sets, where only the gender of the subject is edited and the background is fixed.
AutoAD: Movie Description in Context
The objective of this paper is an automatic Audio Description (AD) model that ingests movies and outputs AD in text form.
AutoAD II: The Sequel - Who, When, and What in Movie Audio Description
Audio Description (AD) is the task of generating descriptions of visual content, at suitable time intervals, for the benefit of visually impaired audiences.
A CLIP-Hitchhiker's Guide to Long Video Retrieval
Our goal in this paper is the adaptation of image-text models for long video retrieval.
Ranked #4 on
Zero-Shot Action Recognition
on Charades
A Prompt Array Keeps the Bias Away: Debiasing Vision-Language Models with Adversarial Learning
Vision-language models can encode societal biases and stereotypes, but there are challenges to measuring and mitigating these multimodal harms due to lacking measurement robustness and feature degradation.
Frozen in Time: A Joint Video and Image Encoder for End-to-End Retrieval
Our objective in this work is video-text retrieval - in particular a joint embedding that enables efficient text-to-video retrieval.
Ranked #4 on
Video Retrieval
on QuerYD
(using extra training data)
Condensed Movies: Story Based Retrieval with Contextual Embeddings
Our objective in this work is long range understanding of the narrative structure of movies.
Count, Crop and Recognise: Fine-Grained Recognition in the Wild
The goal of this paper is to label all the animal individuals present in every frame of a video.
