most citedMeta-Learning Hyperparameters for Parameter Efficient Fine-Tuning

7 citations · 7 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CV2026

FreeOrbit4D: Training-Free Arbitrary Camera Redirection for Monocular Videos via Foreground-Complete 4D Reconstruction

Wei Cao, Hao Zhang, Fengrui Tian +5

Camera redirection aims to replay a dynamic scene from a single monocular video under a user-specified camera trajectory. However, large-angle redirection is inherently ill-posed:…

cs.LG20267 cited

Meta-Learning Hyperparameters for Parameter Efficient Fine-Tuning

Zichen Tian, Yaoyao Liu, Qianru Sun

Training large foundation models from scratch for domain-specific applications is almost impossible due to data limits and long-tailed distributions -- taking remote sensing (RS) a…

cs.CV2024

HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting

Yuanhao Cai, Zihao Xiao, Yixun Liang +5

High dynamic range (HDR) novel view synthesis (NVS) aims to create photorealistic images from novel viewpoints using HDR imaging techniques. The rendered HDR images capture a wider…

cs.CV2024

iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning

Tom Fischer, Yaoyao Liu, Artur Jesslen +6

Different from human nature, it is still common practice today for vision tasks to train deep learning models only initially and on fixed datasets. A variety of approaches have rec…

cs.CV2024

ImageNet3D: Towards General-Purpose Object-Level 3D Understanding

Wufei Ma, Guanning Zeng, Guofeng Zhang +5

A vision model with general-purpose object-level 3D understanding should be capable of inferring both 2D (e.g., class name and bounding box) and 3D information (e.g., 3D location a…