most citedOpen-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization

6 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

Propose, Assess, Search: Harnessing LLMs for Goal-Oriented Planning in Instructional Videos

Md Mohaiminul Islam, Tushar Nagarajan, Huiyu Wang +4

Goal-oriented planning, or anticipating a series of actions that transition an agent from its current state to a predefined objective, is crucial for developing intelligent assista…

cs.CV2023

Building an Open-Vocabulary Video CLIP Model with Better Architectures, Optimization and Data

Zuxuan Wu, Zejia Weng, Wujian Peng +4

Despite significant results achieved by Contrastive Language-Image Pretraining (CLIP) in zero-shot image recognition, limited effort has been made exploring its potential for zero-…

cs.CV20231 cited

Towards Scalable Neural Representation for Diverse Videos

Bo He, Xitong Yang, Hanyu Wang +6

Implicit neural representations (INR) have gained increasing attention in representing 3D scenes and images, and have been recently applied to encode videos (e.g., NeRV, E-NeRV). W…

cs.CV20231 cited

MINOTAUR: Multi-task Video Grounding From Multimodal Queries

Raghav Goyal, Effrosyni Mavroudi, Xitong Yang +5

Video understanding tasks take many forms, from action detection to visual query localization and spatio-temporal grounding of sentences. These tasks differ in the type of inputs (…

cs.CV20236 cited

Open-VCLIP: Transforming CLIP to an Open-vocabulary Video Model via Interpolated Weight Optimization

Zejia Weng, Xitong Yang, Ang Li +2

Contrastive Language-Image Pretraining (CLIP) has demonstrated impressive zero-shot learning abilities for image understanding, yet limited effort has been made to investigate CLIP…

cs.CV2023

Vision Transformers Are Good Mask Auto-Labelers

Shiyi Lan, Xitong Yang, Zhiding Yu +3

We propose Mask Auto-Labeler (MAL), a high-quality Transformer-based mask auto-labeling framework for instance segmentation using only box annotations. MAL takes box-cropped images…