activity
20212024
most citediCaps: Iterative Category-level Object Pose and Shape Estimation

4 citations · 9 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20241 cited

Deep Dependency Networks and Advanced Inference Schemes for Multi-Label Classification

Shivvrat Arya, Yu Xiang, Vibhav Gogate

We present a unified framework called deep dependency networks (DDNs) that combines dependency networks and deep learning architectures for multi-label classification, with a parti…

cs.CV2023

Q: How to Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!

Zaid Khan, Vijay Kumar BG, Samuel Schulter +3

Finetuning a large vision language model (VLM) on a target dataset after large scale pretraining is a dominant paradigm in visual question answering (VQA). Datasets for specialized…

cs.CV20233 cited

Selective Structured State-Spaces for Long-Form Video Understanding

Jue Wang, Wentao Zhu, Pichao Wang +4

Effective modeling of complex spatiotemporal dependencies in long-form videos remains an open problem. The recently proposed Structured State-Space Sequence (S4) model with its lin…

cs.CV20221 cited

Few-shot Single-view 3D Reconstruction with Memory Prior Contrastive Network

Zhen Xing, Yijiang Chen, Zhixin Ling +2

3D reconstruction of novel categories based on few-shot learning is appealing in real-world applications and attracts increasing research interests. Previous approaches mainly focu…

cs.CV20214 cited

iCaps: Iterative Category-level Object Pose and Shape Estimation

Xinke Deng, Junyi Geng, Timothy Bretl +2

This paper proposes a category-level 6D object pose and shape estimation approach iCaps, which allows tracking 6D poses of unseen objects in a category and estimating their 3D shap…