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Fan Liang

4 accepted papers

2024

Efficient Point Cloud Attribute Compression Using Rich Parallelizable Context Model

ICASSP 2024accepted

The autoregressive context model has been proven effective in point cloud attribute compression. However, it suffers from unbearable decoding latency due to the limitations of serial decoding and the large scale of point clouds. In this paper, we propose a rich, parallelizable context model for poin…

Cited by 0SourceScholar
2023

Adaptive Sparse Pairwise Loss for Object Re-Identification

CVPR 2023poster

Object re-identification (ReID) aims to find instances with the same identity as the given probe from a large gallery. Pairwise losses play an important role in training a strong ReID network. Existing pairwise losses densely exploit each instance as an anchor and sample its triplets in a mini-batch…

2021

Learning Neural Templates for Recommender Dialogue System

EMNLP 2021main

The task of Conversational Recommendation System (CRS), i.e., recommender dialog system, aims to recommend precise items to users through natural language interactions. Though recent end-to-end neural models have shown promising progress on this task, two key challenges still remain. First, the reco…

2021

Maria: A Visual Experience Powered Conversational Agent

ACL 2021long

Arguably, the visual perception of conversational agents to the physical world is a key way for them to exhibit the human-like intelligence. Image-grounded conversation is thus proposed to address this challenge. Existing works focus on exploring the multimodal dialog models that ground the conversa…