4 citations · 7 across the 14 of their papers we have counts for
13 papers · 1 filter
Thinking With Tools, Not With Pixels: Tool Calls as Text Scaffolds for Visual Reasoning
Jiahao Shao, Yuanbo Yang, Yiyi Liao +3
Tool-augmented vision-language models increasingly "think with images": they call crop, zoom, or code tools and reason over the returned pixels. However, recent work using blind te…
GARDEN: Gravity-Aligned Reconstruction of Disentangled ENvironments from RGB images
Jiahao Sun, Dingkun Wei, Zehong Shen +3
Converting multi-view RGB observations into simulation-ready 3D environments remains challenging because current reconstruction pipelines produce monolithic scene representations w…
AAD-1: Asymmetric Adversarial Distillation for One-Step Autoregressive Video Generation
Haobo Li, Yanhong Zeng, Yunhong Lu +6
We present AAD-1, an Asymmetric Adversarial Distillation framework for One-step autoregressive image-to-video generation. State-of-the-art methods adopt adversarial distillation bu…
ScenDi: 3D-to-2D Scene Diffusion Cascades for Urban Generation
Hanlei Guo, Jiahao Shao, Xinya Chen +4
Recent advancements in 3D object generation using diffusion models have achieved remarkable success, but generating realistic 3D urban scenes remains challenging. Existing methods…
Orientation Matters: Making 3D Generative Models Orientation-Aligned
Yichong Lu, Yuzhuo Tian, Zijin Jiang +7
Humans intuitively perceive object shape and orientation from a single image, guided by strong priors about canonical poses. However, existing 3D generative models often produce mi…
FLARE: Feed-forward Geometry, Appearance and Camera Estimation from Uncalibrated Sparse Views
Shangzhan Zhang, Jianyuan Wang, Yinghao Xu +5
We present FLARE, a feed-forward model designed to infer high-quality camera poses and 3D geometry from uncalibrated sparse-view images (i.e., as few as 2-8 inputs), which is a cha…
Prometheus: 3D-Aware Latent Diffusion Models for Feed-Forward Text-to-3D Scene Generation
Yuanbo Yang, Jiahao Shao, Xinyang Li +3
In this work, we introduce Prometheus, a 3D-aware latent diffusion model for text-to-3D generation at both object and scene levels in seconds. We formulate 3D scene generation as m…
PlanarSplatting: Accurate Planar Surface Reconstruction in 3 Minutes
Bin Tan, Rui Yu, Yujun Shen +1
This paper presents PlanarSplatting, an ultra-fast and accurate surface reconstruction approach for multiview indoor images. We take the 3D planes as the main objective due to thei…
Learning Temporally Consistent Video Depth from Video Diffusion Priors
Jiahao Shao, Yuanbo Yang, Hongyu Zhou +6
This work addresses the challenge of streamed video depth estimation, which expects not only per-frame accuracy but, more importantly, cross-frame consistency. We argue that sharin…
InFusion: Inpainting 3D Gaussians via Learning Depth Completion from Diffusion Prior
Zhiheng Liu, Hao Ouyang, Qiuyu Wang +7
3D Gaussians have recently emerged as an efficient representation for novel view synthesis. This work studies its editability with a particular focus on the inpainting task, which…
SpatialTracker: Tracking Any 2D Pixels in 3D Space
Yuxi Xiao, Qianqian Wang, Shangzhan Zhang +4
Recovering dense and long-range pixel motion in videos is a challenging problem. Part of the difficulty arises from the 3D-to-2D projection process, leading to occlusions and disco…
MaPa: Text-driven Photorealistic Material Painting for 3D Shapes
Shangzhan Zhang, Shangzan Zhang, Sida Peng +8
This paper aims to generate materials for 3D meshes from text descriptions. Unlike existing methods that synthesize texture maps, we propose to generate segment-wise procedural mat…
Learning 3D-Aware GANs from Unposed Images with Template Feature Field
Xinya Chen, Hanlei Guo, Yanrui Bin +5
Collecting accurate camera poses of training images has been shown to well serve the learning of 3D-aware generative adversarial networks (GANs) yet can be quite expensive in pract…