most citedPointGPT: Auto-regressively Generative Pre-training from Point Clouds

33 citations · 43 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20231 cited

Album Storytelling with Iterative Story-aware Captioning and Large Language Models

Munan Ning, Yujia Xie, Dongdong Chen +5

This work studies how to transform an album to vivid and coherent stories, a task we refer to as "album storytelling". While this task can help preserve memories and facilitate exp…

cs.CV202333 cited

PointGPT: Auto-regressively Generative Pre-training from Point Clouds

Guangyan Chen, Meiling Wang, Yi Yang +3

Large language models (LLMs) based on the generative pre-training transformer (GPT) have demonstrated remarkable effectiveness across a diverse range of downstream tasks. Inspired…

cs.CV2023

Text-Video Retrieval with Disentangled Conceptualization and Set-to-Set Alignment

Peng Jin, Hao Li, Zesen Cheng +5

Text-video retrieval is a challenging cross-modal task, which aims to align visual entities with natural language descriptions. Current methods either fail to leverage the local de…

cs.CV20236 cited

Learning with Fantasy: Semantic-Aware Virtual Contrastive Constraint for Few-Shot Class-Incremental Learning

Zeyin Song, Yifan Zhao, Yujun Shi +3

Few-shot class-incremental learning (FSCIL) aims at learning to classify new classes continually from limited samples without forgetting the old classes. The mainstream framework t…

cs.CV20233 cited

Video-Text as Game Players: Hierarchical Banzhaf Interaction for Cross-Modal Representation Learning

Peng Jin, Jinfa Huang, Pengfei Xiong +5

Contrastive learning-based video-language representation learning approaches, e.g., CLIP, have achieved outstanding performance, which pursue semantic interaction upon pre-defined…