116 citations · 384 across the 39 of their papers we have counts for
35 papers · 1 filter
Event ActivityNet: A Large-Scale Simulated-Event Benchmark for Untrimmed Action Understanding
Cheng-Yao Hong, Ting-Wei Lin, Yun-Chung Lai +3
Long-horizon event-based action understanding remains underexplored because existing datasets largely comprise short, trimmed clips, while collecting native event streams with dens…
R2SM: Referring and Reasoning for Selective Masks
Yu-Lin Shih, Wei-En Tai, Cheng Sun +2
We introduce a new task, Referring and Reasoning for Selective Masks (R2SM), which extends text-guided segmentation by incorporating mask-type selection driven by user intent. This…
ErpGS: Equirectangular Image Rendering enhanced with 3D Gaussian Regularization
Shintaro Ito, Natsuki Takama, Koichi Ito +2
The use of multi-view images acquired by a 360-degree camera can reconstruct a 3D space with a wide area. There are 3D reconstruction methods from equirectangular images based on N…
Sparse2DGS: Sparse-View Surface Reconstruction using 2D Gaussian Splatting with Dense Point Cloud
Natsuki Takama, Shintaro Ito, Koichi Ito +2
Gaussian Splatting (GS) has gained attention as a fast and effective method for novel view synthesis. It has also been applied to 3D reconstruction using multi-view images and can…
OB3D: A New Dataset for Benchmarking Omnidirectional 3D Reconstruction Using Blender
Shintaro Ito, Natsuki Takama, Toshiki Watanabe +3
Recent advancements in radiance field rendering, exemplified by Neural Radiance Fields (NeRF) and 3D Gaussian Splatting (3DGS), have significantly progressed 3D modeling and recons…
EigenGS Representation: From Eigenspace to Gaussian Image Space
Lo-Wei Tai, Ching-En Li, Cheng-Lin Chen +3
Principal Component Analysis (PCA), a classical dimensionality reduction technique, and 2D Gaussian representation, an adaptation of 3D Gaussian Splatting for image representation,…
Segment Anything, Even Occluded
Wei-En Tai, Yu-Lin Shih, Cheng Sun +2
Amodal instance segmentation, which aims to detect and segment both visible and invisible parts of objects in images, plays a crucial role in various applications including autonom…
DiffusionAtlas: High-Fidelity Consistent Diffusion Video Editing
Shao-Yu Chang, Hwann-Tzong Chen, Tyng-Luh Liu
We present a diffusion-based video editing framework, namely DiffusionAtlas, which can achieve both frame consistency and high fidelity in editing video object appearance. Despite…
Seg2Reg: Differentiable 2D Segmentation to 1D Regression Rendering for 360 Room Layout Reconstruction
Cheng Sun, Wei-En Tai, Yu-Lin Shih +5
State-of-the-art single-view 360-degree room layout reconstruction methods formulate the problem as a high-level 1D (per-column) regression task. On the other hand, traditional low…
Hashing Neural Video Decomposition with Multiplicative Residuals in Space-Time
Cheng-Hung Chan, Cheng-Yang Yuan, Cheng Sun +1
We present a video decomposition method that facilitates layer-based editing of videos with spatiotemporally varying lighting and motion effects. Our neural model decomposes an inp…
Multiview Regenerative Morphing with Dual Flows
Chih-Jung Tsai, Cheng Sun, Hwann-Tzong Chen
This paper aims to address a new task of image morphing under a multiview setting, which takes two sets of multiview images as the input and generates intermediate renderings that…
Mask2Hand: Learning to Predict the 3D Hand Pose and Shape from Shadow
Li-Jen Chang, Yu-Cheng Liao, Chia-Hui Lin +1
We present a self-trainable method, Mask2Hand, which learns to solve the challenging task of predicting 3D hand pose and shape from a 2D binary mask of hand silhouette/shadow witho…
Self-supervised 360 Room Layout Estimation
Hao-Wen Ting, Cheng Sun, Hwann-Tzong Chen
We present the first self-supervised method to train panoramic room layout estimation models without any labeled data. Unlike per-pixel dense depth that provides abundant correspon…
Pose Adaptive Dual Mixup for Few-Shot Single-View 3D Reconstruction
Ta-Ying Cheng, Hsuan-Ru Yang, Niki Trigoni +2
We present a pose adaptive few-shot learning procedure and a two-stage data interpolation regularization, termed Pose Adaptive Dual Mixup (PADMix), for single-image 3D reconstructi…
Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstruction
Cheng Sun, Min Sun, Hwann-Tzong Chen
We present a super-fast convergence approach to reconstructing the per-scene radiance field from a set of images that capture the scene with known poses. This task, which is often…
Specialize and Fuse: Pyramidal Output Representation for Semantic Segmentation
Chi-Wei Hsiao, Cheng Sun, Hwann-Tzong Chen +1
We present a novel pyramidal output representation to ensure parsimony with our "specialize and fuse" process for semantic segmentation. A pyramidal "output" representation consist…
Moving in a 360 World: Synthesizing Panoramic Parallaxes from a Single Panorama
Ching-Yu Hsu, Cheng Sun, Hwann-Tzong Chen
We present Omnidirectional Neural Radiance Fields (OmniNeRF), the first method to the application of parallax-enabled novel panoramic view synthesis. Recent works for novel view sy…
Indoor Panorama Planar 3D Reconstruction via Divide and Conquer
Cheng Sun, Chi-Wei Hsiao, Ning-Hsu Wang +2
Indoor panorama typically consists of human-made structures parallel or perpendicular to gravity. We leverage this phenomenon to approximate the scene in a 360-degree image with (H…
DropLoss for Long-Tail Instance Segmentation
Ting-I Hsieh, Esther Robb, Hwann-Tzong Chen +1
Long-tailed class distributions are prevalent among the practical applications of object detection and instance segmentation. Prior work in long-tail instance segmentation addresse…
HoHoNet: 360 Indoor Holistic Understanding with Latent Horizontal Features
Cheng Sun, Min Sun, Hwann-Tzong Chen
We present HoHoNet, a versatile and efficient framework for holistic understanding of an indoor 360-degree panorama using a Latent Horizontal Feature (LHFeat). The compact LHFeat f…
Learning Camera-Aware Noise Models
Ke-Chi Chang, Ren Wang, Hung-Jin Lin +4
Modeling imaging sensor noise is a fundamental problem for image processing and computer vision applications. While most previous works adopt statistical noise models, real-world n…
Learning Gaussian Instance Segmentation in Point Clouds
Shih-Hung Liu, Shang-Yi Yu, Shao-Chi Wu +2
This paper presents a novel method for instance segmentation of 3D point clouds. The proposed method is called Gaussian Instance Center Network (GICN), which can approximate the di…
Silhouette-Net: 3D Hand Pose Estimation from Silhouettes
Kuo-Wei Lee, Shih-Hung Liu, Hwann-Tzong Chen +1
3D hand pose estimation has received a lot of attention for its wide range of applications and has made great progress owing to the development of deep learning. Existing approache…
One-Shot Object Detection with Co-Attention and Co-Excitation
Ting-I Hsieh, Yi-Chen Lo, Hwann-Tzong Chen +1
This paper aims to tackle the challenging problem of one-shot object detection. Given a query image patch whose class label is not included in the training data, the goal of the ta…