most citedSiNeRF: Sinusoidal Neural Radiance Fields for Joint Pose Estimation and Scene Reconstruction

10 citations · 14 across the 7 of their papers we have counts for

collaborators

21 papers

cs.CV202317 cited

Towards High-quality HDR Deghosting with Conditional Diffusion Models

Qingsen Yan, Tao Hu, Yuan Sun +5

High Dynamic Range (HDR) images can be recovered from several Low Dynamic Range (LDR) images by existing Deep Neural Networks (DNNs) techniques. Despite the remarkable progress, DN…

cs.LG20234 cited

Does Graph Distillation See Like Vision Dataset Counterpart?

Beining Yang, Kai Wang, Qingyun Sun +5

Training on large-scale graphs has achieved remarkable results in graph representation learning, but its cost and storage have attracted increasing concerns. Existing graph condens…

cs.CV20232 cited

Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day

Yifan Jiang, Hao Tang, Jen-Hao Rick Chang +3

The task of novel view synthesis aims to generate unseen perspectives of an object or scene from a limited set of input images. Nevertheless, synthesizing novel views from a single…

cs.CV20231 cited

Temporal-aware Hierarchical Mask Classification for Video Semantic Segmentation

Zhaochong An, Guolei Sun, Zongwei Wu +2

Modern approaches have proved the huge potential of addressing semantic segmentation as a mask classification task which is widely used in instance-level segmentation. This paradig…

cs.CV20231 cited

UniTR: A Unified and Efficient Multi-Modal Transformer for Bird's-Eye-View Representation

Haiyang Wang, Hao Tang, Shaoshuai Shi +4

Jointly processing information from multiple sensors is crucial to achieving accurate and robust perception for reliable autonomous driving systems. However, current 3D perception…

cs.CV202310 cited

Enlighten Anything: When Segment Anything Model Meets Low-Light Image Enhancement

Qihan Zhao, Xiaofeng Zhang, Hao Tang +2

Image restoration is a low-level visual task, and most CNN methods are designed as black boxes, lacking transparency and intrinsic aesthetics. Many unsupervised approaches ignore t…