80 citations · 188 across the 39 of their papers we have counts for
41 papers
GeT: Generative Target Structure Debiasing for Domain Adaptation
Can Zhang, Gim Hee Lee
Domain adaptation (DA) aims to transfer knowledge from a fully labeled source to a scarcely labeled or totally unlabeled target under domain shift. Recently, semi-supervised learni…
DReg-NeRF: Deep Registration for Neural Radiance Fields
Yu Chen, Gim Hee Lee
Although Neural Radiance Fields (NeRF) is popular in the computer vision community recently, registering multiple NeRFs has yet to gain much attention. Unlike the existing work, Ne…
GHuNeRF: Generalizable Human NeRF from a Monocular Video
Chen Li, Jiahao Lin, Gim Hee Lee
In this paper, we tackle the challenging task of learning a generalizable human NeRF model from a monocular video. Although existing generalizable human NeRFs have achieved impress…
NU-MCC: Multiview Compressive Coding with Neighborhood Decoder and Repulsive UDF
Stefan Lionar, Xiangyu Xu, Min Lin +1
Remarkable progress has been made in 3D reconstruction from single-view RGB-D inputs. MCC is the current state-of-the-art method in this field, which achieves unprecedented success…
OD-NeRF: Efficient Training of On-the-Fly Dynamic Neural Radiance Fields
Zhiwen Yan, Chen Li, Gim Hee Lee
Dynamic neural radiance fields (dynamic NeRFs) have demonstrated impressive results in novel view synthesis on 3D dynamic scenes. However, they often require complete video sequenc…
Boosting Long-tailed Object Detection via Step-wise Learning on Smooth-tail Data
Na Dong, Yongqiang Zhang, Mingli Ding +1
Real-world data tends to follow a long-tailed distribution, where the class imbalance results in dominance of the head classes during training. In this paper, we propose a frustrat…
ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis
Shoukang Hu, Kaichen Zhou, Kaiyu Li +6
Neural Radiance Fields (NeRF) has demonstrated remarkable 3D reconstruction capabilities with dense view images. However, its performance significantly deteriorates under sparse vi…
Make-A-Protagonist: Generic Video Editing with An Ensemble of Experts
Yuyang Zhao, Enze Xie, Lanqing Hong +2
The text-driven image and video diffusion models have achieved unprecedented success in generating realistic and diverse content. Recently, the editing and variation of existing im…
Overcoming the Trade-off Between Accuracy and Plausibility in 3D Hand Shape Reconstruction
Ziwei Yu, Chen Li, Linlin Yang +4
Direct mesh fitting for 3D hand shape reconstruction is highly accurate. However, the reconstructed meshes are prone to artifacts and do not appear as plausible hand shapes. Conver…
ScarceNet: Animal Pose Estimation with Scarce Annotations
Chen Li, Gim Hee Lee
Animal pose estimation is an important but under-explored task due to the lack of labeled data. In this paper, we tackle the task of animal pose estimation with scarce annotations,…
DBARF: Deep Bundle-Adjusting Generalizable Neural Radiance Fields
Yu Chen, Gim Hee Lee
Recent works such as BARF and GARF can bundle adjust camera poses with neural radiance fields (NeRF) which is based on coordinate-MLPs. Despite the impressive results, these method…
NeRF-DS: Neural Radiance Fields for Dynamic Specular Objects
Zhiwen Yan, Chen Li, Gim Hee Lee
Dynamic Neural Radiance Field (NeRF) is a powerful algorithm capable of rendering photo-realistic novel view images from a monocular RGB video of a dynamic scene. Although it warps…
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning
Hao Yang, Lanqing Hong, Aoxue Li +4
Although many recent works have investigated generalizable NeRF-based novel view synthesis for unseen scenes, they seldom consider the synthetic-to-real generalization, which is de…
AdaSfM: From Coarse Global to Fine Incremental Adaptive Structure from Motion
Yu Chen, Zihao Yu, Shu Song +3
Despite the impressive results achieved by many existing Structure from Motion (SfM) approaches, there is still a need to improve the robustness, accuracy, and efficiency on large-…
Synthetic-to-Real Domain Generalized Semantic Segmentation for 3D Indoor Point Clouds
Yuyang Zhao, Na Zhao, Gim Hee Lee
Semantic segmentation in 3D indoor scenes has achieved remarkable performance under the supervision of large-scale annotated data. However, previous works rely on the assumption th…
Open World DETR: Transformer based Open World Object Detection
Na Dong, Yongqiang Zhang, Mingli Ding +1
Open world object detection aims at detecting objects that are absent in the object classes of the training data as unknown objects without explicit supervision. Furthermore, the e…
UNIKD: UNcertainty-filtered Incremental Knowledge Distillation for Neural Implicit Representation
Mengqi Guo, Chen Li, Hanlin Chen +1
Recent neural implicit representations (NIRs) have achieved great success in the tasks of 3D reconstruction and novel view synthesis. However, they require the images of a scene fr…
Style-Hallucinated Dual Consistency Learning: A Unified Framework for Visual Domain Generalization
Yuyang Zhao, Zhun Zhong, Na Zhao +2
Domain shift widely exists in the visual world, while modern deep neural networks commonly suffer from severe performance degradation under domain shift due to the poor generalizat…
Motion and Context-Aware Audio-Visual Conditioned Video Prediction
Yating Xu, Conghui Hu, Gim Hee Lee
The existing state-of-the-art method for audio-visual conditioned video prediction uses the latent codes of the audio-visual frames from a multimodal stochastic network and a frame…
Feature Representation Learning for Unsupervised Cross-domain Image Retrieval
Conghui Hu, Gim Hee Lee
Current supervised cross-domain image retrieval methods can achieve excellent performance. However, the cost of data collection and labeling imposes an intractable barrier to pract…
Rethinking IoU-based Optimization for Single-stage 3D Object Detection
Hualian Sheng, Sijia Cai, Na Zhao +5
Since Intersection-over-Union (IoU) based optimization maintains the consistency of the final IoU prediction metric and losses, it has been widely used in both regression and class…
NeurAR: Neural Uncertainty for Autonomous 3D Reconstruction with Implicit Neural Representations
Yunlong Ran, Jing Zeng, Shibo He +5
Implicit neural representations have shown compelling results in offline 3D reconstruction and also recently demonstrated the potential for online SLAM systems. However, applying t…
Adversarial Style Augmentation for Domain Generalized Urban-Scene Segmentation
Zhun Zhong, Yuyang Zhao, Gim Hee Lee +1
In this paper, we consider the problem of domain generalization in semantic segmentation, which aims to learn a robust model using only labeled synthetic (source) data. The model i…
CA-UDA: Class-Aware Unsupervised Domain Adaptation with Optimal Assignment and Pseudo-Label Refinement
Can Zhang, Gim Hee Lee
Recent works on unsupervised domain adaptation (UDA) focus on the selection of good pseudo-labels as surrogates for the missing labels in the target data. However, source domain bi…