activity
20172023
most citedThe AVA-Kinetics Localized Human Actions Video Dataset

84 citations · 264 across the 17 of their papers we have counts for

collaborators
Showing 2023Show all

6 papers · 1 filter

cs.CV2023★ 2 cited

UnLoc: A Unified Framework for Video Localization Tasks

Shen Yan, Xuehan Xiong, Arsha Nagrani +5

While large-scale image-text pretrained models such as CLIP have been used for multiple video-level tasks on trimmed videos, their use for temporal localization in untrimmed videos…

cs.CV2023★ 10 cited

DaTaSeg: Taming a Universal Multi-Dataset Multi-Task Segmentation Model

Xiuye Gu, Yin Cui, Jonathan Huang +8

Observing the close relationship among panoptic, semantic and instance segmentation tasks, we propose to train a universal multi-dataset multi-task segmentation model: DaTaSeg.We u…

cs.CV2023★ 7 cited

SPAE: Semantic Pyramid AutoEncoder for Multimodal Generation with Frozen LLMs

Lijun Yu, Yong Cheng, Zhiruo Wang +10

In this work, we introduce Semantic Pyramid AutoEncoder (SPAE) for enabling frozen LLMs to perform both understanding and generation tasks involving non-linguistic modalities such…

cs.CV2023★ 15 cited

AVIS: Autonomous Visual Information Seeking with Large Language Model Agent

Ziniu Hu, Ahmet Iscen, Chen Sun +5

In this paper, we propose an autonomous information seeking visual question answering framework, AVIS. Our method leverages a Large Language Model (LLM) to dynamically strategize t…

cs.CV2023

IC3: Image Captioning by Committee Consensus

David M. Chan, Austin Myers, Sudheendra Vijayanarasimhan +2

If you ask a human to describe an image, they might do so in a thousand different ways. Traditionally, image captioning models are trained to generate a single "best" (most like a…

cs.CV2023

Open-Vocabulary Temporal Action Detection with Off-the-Shelf Image-Text Features

Vivek Rathod, Bryan Seybold, Sudheendra Vijayanarasimhan +4

Detecting actions in untrimmed videos should not be limited to a small, closed set of classes. We present a simple, yet effective strategy for open-vocabulary temporal action detec…