1 citations · 2 across the 14 of their papers we have counts for
14 papers
Visual Words Meet BM25: Sparse Auto-Encoder Visual Word Scoring for Image Retrieval
Donghoon Han, Eunhwan Park, Seunghyeon Seo
Dense image retrieval is accurate but offers limited interpretability and attribution, and it can be compute-intensive at scale. We present \textbf{BM25-V}, which applies Okapi BM2…
LoGoColor: Local-Global 3D Colorization for 360° Scenes
Yeonjin Chang, Juhwan Cho, Seunghyeon Seo +2
Single-channel 3D reconstruction is widely used in fields such as robotics and medical imaging. While these methods are good at reconstructing 3D geometry, their outputs are typica…
Generative Head-Mounted Camera Captures for Photorealistic Avatars
Shaojie Bai, Seunghyeon Seo, Yida Wang +8
Enabling photorealistic avatar animations in virtual and augmented reality (VR/AR) has been challenging because of the difficulty of obtaining ground truth state of faces. It is ph…
DivCon-NeRF: Diverse and Consistent Ray Augmentation for Few-Shot NeRF
Ingyun Lee, Jae Won Jang, Seunghyeon Seo +1
Neural Radiance Field (NeRF) has shown remarkable performance in novel view synthesis but requires numerous multi-view images, limiting its practicality in few-shot scenarios. Ray…
ROODI: Reconstructing Occluded Objects with Denoising Inpainters
Yeonjin Chang, Erqun Dong, Seunghyeon Seo +2
While the quality of novel-view images has improved dramatically with 3D Gaussian Splatting, extracting specific objects from scenes remains challenging. Isolating individual 3D Ga…
Unleash the Potential of CLIP for Video Highlight Detection
Donghoon Han, Seunghyeon Seo, Eunhwan Park +2
Multimodal and large language models (LLMs) have revolutionized the utilization of open-world knowledge, unlocking novel potentials across various tasks and applications. Among the…
ARC-NeRF: Area Ray Casting for Broader Unseen View Coverage in Few-shot Object Rendering
Seunghyeon Seo, Yeonjin Chang, Jayeon Yoo +3
Recent advancements in the Neural Radiance Field (NeRF) have enhanced its capabilities for novel view synthesis, yet its reliance on dense multi-view training images poses a practi…
Fast Sun-aligned Outdoor Scene Relighting based on TensoRF
Yeonjin Chang, Yearim Kim, Seunghyeon Seo +2
In this work, we introduce our method of outdoor scene relighting for Neural Radiance Fields (NeRF) named Sun-aligned Relighting TensoRF (SR-TensoRF). SR-TensoRF offers a lightweig…
ConcatPlexer: Additional Dim1 Batching for Faster ViTs
Donghoon Han, Seunghyeon Seo, Donghyeon Jeon +3
Transformers have demonstrated tremendous success not only in the natural language processing (NLP) domain but also the field of computer vision, igniting various creative approach…
FlipNeRF: Flipped Reflection Rays for Few-shot Novel View Synthesis
Seunghyeon Seo, Yeonjin Chang, Nojun Kwak
Neural Radiance Field (NeRF) has been a mainstream in novel view synthesis with its remarkable quality of rendered images and simple architecture. Although NeRF has been developed…
MixNeRF: Modeling a Ray with Mixture Density for Novel View Synthesis from Sparse Inputs
Seunghyeon Seo, Donghoon Han, Yeonjin Chang +1
Neural Radiance Field (NeRF) has broken new ground in the novel view synthesis due to its simple concept and state-of-the-art quality. However, it suffers from severe performance d…
MDPose: Real-Time Multi-Person Pose Estimation via Mixture Density Model
Seunghyeon Seo, Jaeyoung Yoo, Jihye Hwang +1
One of the major challenges in multi-person pose estimation is instance-aware keypoint estimation. Previous methods address this problem by leveraging an off-the-shelf detector, he…
End-to-End Multi-Object Detection with a Regularized Mixture Model
Jaeyoung Yoo, Hojun Lee, Seunghyeon Seo +2
Recent end-to-end multi-object detectors simplify the inference pipeline by removing hand-crafted processes such as non-maximum suppression (NMS). However, during training, they st…
MUM : Mix Image Tiles and UnMix Feature Tiles for Semi-Supervised Object Detection
JongMok Kim, Jooyoung Jang, Seunghyeon Seo +3
Many recent semi-supervised learning (SSL) studies build teacher-student architecture and train the student network by the generated supervisory signal from the teacher. Data augme…