Search Results for author:
Found 3 papers, 3 papers with code
OST: Refining Text Knowledge with Optimal Spatio-Temporal Descriptor for General Video Recognition
Due to the resource-intensive nature of training vision-language models on expansive video data, a majority of studies have centered on adapting pre-trained image-language models to the video domain.
Ranked #2 on
Zero-Shot Action Recognition
on Kinetics
First Place Solution to the CVPR'2023 AQTC Challenge: A Function-Interaction Centric Approach with Spatiotemporal Visual-Language Alignment
Affordance-Centric Question-driven Task Completion (AQTC) has been proposed to acquire knowledge from videos to furnish users with comprehensive and systematic instructions.
AShapeFormer: Semantics-Guided Object-Level Active Shape Encoding for 3D Object Detection via Transformers
In this work, we propose AShapeFormer, a semantics-guided object-level shape encoding module for 3D object detection.
