75 citations · 136 across the 12 of their papers we have counts for
13 papers
4DAnyone: Create Anyone in 4D from a Casual Monocular Video
Yudong Jin, Tao Xie, Qihang Zhang +6
We present 4DAnyone, a framework for reconstructing 4D humans from an uncalibrated monocular video by generating reconstruction-grade multiview-consistent videos and lifting them i…
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…
PointSplat: Compact Gaussian Splatting via Human-Centric Prediction
Yujie Guo, Yudong Jin, Lingteng Qiu +7
Producing 3D human representations from input views on the fly is essential for immersive live streaming systems, where representation compactness is as critical as high fidelity g…
Natural Human Motion Recovery by Aligning High-Order Temporal Dynamics from Monocular Videos
Dingkun Wei, Zehong Shen, Yan Xia +3
Human motion recovered from monocular videos often appears overly smooth or dynamically inconsistent, even when joint positions are numerically accurate. We observe that this limit…
Advancing Open-source World Models
Robbyant Team, Zelin Gao, Qiuyu Wang +21
We present LingBot-World, an open-sourced world simulator stemming from video generation. Positioned as a top-tier world model, LingBot-World offers the following features. (1) It…
MatchAnything: Universal Cross-Modality Image Matching with Large-Scale Pre-Training
Xingyi He, Hao Yu, Sida Peng +4
Image matching, which aims to identify corresponding pixel locations between images, is crucial in a wide range of scientific disciplines, aiding in image registration, fusion, and…
Motion-2-To-3: Leveraging 2D Motion Data for 3D Motion Generations
Ruoxi Guo, Huaijin Pi, Zehong Shen +8
Text-driven human motion synthesis has showcased its potential for revolutionizing motion design in the movie and game industry. Existing methods often rely on 3D motion capture da…
World-Grounded Human Motion Recovery via Gravity-View Coordinates
Zehong Shen, Huaijin Pi, Yan Xia +6
We present a novel method for recovering world-grounded human motion from monocular video. The main challenge lies in the ambiguity of defining the world coordinate system, which v…
Generating Human Motion in 3D Scenes from Text Descriptions
Zhi Cen, Huaijin Pi, Sida Peng +5
Generating human motions from textual descriptions has gained growing research interest due to its wide range of applications. However, only a few works consider human-scene intera…
Learning Human Mesh Recovery in 3D Scenes
Zehong Shen, Zhi Cen, Sida Peng +3
We present a novel method for recovering the absolute pose and shape of a human in a pre-scanned scene given a single image. Unlike previous methods that perform sceneaware mesh op…
Long-term Visual Localization with Mobile Sensors
Shen Yan, Yu Liu, Long Wang +6
Despite the remarkable advances in image matching and pose estimation, image-based localization of a camera in a temporally-varying outdoor environment is still a challenging probl…
LoFTR: Detector-Free Local Feature Matching with Transformers
Jiaming Sun, Zehong Shen, Yuang Wang +2
We present a novel method for local image feature matching. Instead of performing image feature detection, description, and matching sequentially, we propose to first establish pix…
GIFT: Learning Transformation-Invariant Dense Visual Descriptors via Group CNNs
Yuan Liu, Zehong Shen, Zhixuan Lin +3
Finding local correspondences between images with different viewpoints requires local descriptors that are robust against geometric transformations. An approach for transformation…