20 citations · 33 across the 11 of their papers we have counts for
14 papers
Reasmory: 3D Reconstruction as Explicit Memory for VLMs Spatial Reasoning
Jixuan He, Xueting Li, Chieh Hubert Lin +1
Vision-Language Models (VLMs) exhibit emerging spatial reasoning capabilities, yet they remain unreliable on tasks requiring precise spatial understanding, such as viewpoint reason…
Skyfall-GS: Synthesizing Immersive 3D Urban Scenes from Satellite Imagery
Jie-Ying Lee, Yi-Ruei Liu, Shr-Ruei Tsai +6
Synthesizing large-scale, explorable, and geometrically accurate 3D urban scenes is a challenging yet valuable task for immersive and embodied applications. The challenge lies in t…
Restage4D: Reanimating Deformable 3D Reconstruction from a Single Video
Jixuan He, Chieh Hubert Lin, Lu Qi +1
Creating deformable 3D content has gained increasing attention with the rise of text-to-image and image-to-video generative models. While these models provide rich semantic priors…
InstaInpaint: Instant 3D-Scene Inpainting with Masked Large Reconstruction Model
Junqi You, Chieh Hubert Lin, Weijie Lyu +2
Recent advances in 3D scene reconstruction enable real-time viewing in virtual and augmented reality. To support interactive operations for better immersiveness, such as moving or…
DGS-LRM: Real-Time Deformable 3D Gaussian Reconstruction From Monocular Videos
Chieh Hubert Lin, Zhaoyang Lv, Songyin Wu +11
We introduce the Deformable Gaussian Splats Large Reconstruction Model (DGS-LRM), the first feed-forward method predicting deformable 3D Gaussian splats from a monocular posed vide…
Towards Affordance-Aware Articulation Synthesis for Rigged Objects
Yu-Chu Yu, Chieh Hubert Lin, Hsin-Ying Lee +3
Rigged objects are commonly used in artist pipelines, as they can flexibly adapt to different scenes and postures. However, articulating the rigs into realistic affordance-aware po…
Taming Latent Diffusion Model for Neural Radiance Field Inpainting
Chieh Hubert Lin, Changil Kim, Jia-Bin Huang +5
Neural Radiance Field (NeRF) is a representation for 3D reconstruction from multi-view images. Despite some recent work showing preliminary success in editing a reconstructed NeRF…
Virtual Pets: Animatable Animal Generation in 3D Scenes
Yen-Chi Cheng, Chieh Hubert Lin, Chaoyang Wang +5
Toward unlocking the potential of generative models in immersive 4D experiences, we introduce Virtual Pet, a novel pipeline to model realistic and diverse motions for target animal…
DreaMo: Articulated 3D Reconstruction From A Single Casual Video
Tao Tu, Ming-Feng Li, Chieh Hubert Lin +3
Articulated 3D reconstruction has valuable applications in various domains, yet it remains costly and demands intensive work from domain experts. Recent advancements in template-fr…
Motion-Conditioned Diffusion Model for Controllable Video Synthesis
Tsai-Shien Chen, Chieh Hubert Lin, Hung-Yu Tseng +2
Recent advancements in diffusion models have greatly improved the quality and diversity of synthesized content. To harness the expressive power of diffusion models, researchers hav…
InfiniCity: Infinite-Scale City Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Willi Menapace +4
Toward infinite-scale 3D city synthesis, we propose a novel framework, InfiniCity, which constructs and renders an unconstrainedly large and 3D-grounded environment from random noi…
Unveiling The Mask of Position-Information Pattern Through the Mist of Image Features
Chieh Hubert Lin, Hsin-Ying Lee, Hung-Yu Tseng +2
Recent studies show that paddings in convolutional neural networks encode absolute position information which can negatively affect the model performance for certain tasks. However…
InfinityGAN: Towards Infinite-Pixel Image Synthesis
Chieh Hubert Lin, Hsin-Ying Lee, Yen-Chi Cheng +2
We present a novel framework, InfinityGAN, for arbitrary-sized image generation. The task is associated with several key challenges. First, scaling existing models to an arbitraril…
In&Out : Diverse Image Outpainting via GAN Inversion
Yen-Chi Cheng, Chieh Hubert Lin, Hsin-Ying Lee +3
Image outpainting seeks for a semantically consistent extension of the input image beyond its available content. Compared to inpainting -- filling in missing pixels in a way cohere…