activity
20202026
most citedGenerating Representative Samples for Few-Shot Classification

12 citations · 12 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2026

Technical Report on the CVPR 2026@AdvML Workshop Challenge

Tianyuan Zhang, Zonglei Jing, Jiangfan Liu +47

Vision-language agents (VLAs) are increasingly used to interpret complex driving scenes and support safety-critical reasoning. This report presents the CVPR 2026@AdvML Workshop Cha…

cs.CV2025

Multi-view Gaze Target Estimation

Qiaomu Miao, Vivek Raju Golani, Jingyi Xu +3

This paper presents a method that utilizes multiple camera views for the gaze target estimation (GTE) task. The approach integrates information from different camera views to impro…

cs.CV2024

Importance-Based Token Merging for Efficient Image and Video Generation

Haoyu Wu, Jingyi Xu, Hieu Le +1

Token merging can effectively accelerate various vision systems by processing groups of similar tokens only once and sharing the results across them. However, existing token groupi…

cs.CV2024

Assessing Sample Quality via the Latent Space of Generative Models

Jingyi Xu, Hieu Le, Dimitris Samaras

Advances in generative models increase the need for sample quality assessment. To do so, previous methods rely on a pre-trained feature extractor to embed the generated samples and…

cs.CV2023

Zero-Shot Object Counting with Language-Vision Models

Jingyi Xu, Hieu Le, Dimitris Samaras

Class-agnostic object counting aims to count object instances of an arbitrary class at test time. It is challenging but also enables many potential applications. Current methods re…

cs.CV2023

Zero-shot Object Counting

Jingyi Xu, Hieu Le, Vu Nguyen +2

Class-agnostic object counting aims to count object instances of an arbitrary class at test time. It is challenging but also enables many potential applications. Current methods re…