2 citations · 3 across the 12 of their papers we have counts for
14 papers
WildRayZer: Self-supervised Large View Synthesis in Dynamic Environments
Xuweiyi Chen, Wentao Zhou, Zezhou Cheng
We present WildRayZer, a self-supervised framework for novel view synthesis (NVS) in dynamic environments where both the camera and objects move. Dynamic content breaks the multi-v…
Next-Embedding Prediction Makes Strong Vision Learners
Sihan Xu, Ziqiao Ma, Wenhao Chai +5
Inspired by the success of generative pretraining in natural language, we ask whether the same principles can yield strong self-supervised visual learners. Instead of training mode…
Stereo4DWalker: Learning 4D-aware Embodied Urban Navigation from Internet Stereo Videos
Wentao Zhou, Xuweiyi Chen, Vignesh Rajagopal +3
Despite rapid progress, embodied navigation in dynamic and unstructured urban environments remains brittle. Most existing approaches directly map monocular visual inputs to actions…
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu +10
Can we scale 4D pretraining to learn general space-time representations that reconstruct an object from a few views at some times to any view at any time? We provide an affirmative…
SAB3R: Semantic-Augmented Backbone in 3D Reconstruction
Xuweiyi Chen, Tian Xia, Sihan Xu +3
We introduce a new task, Map and Locate, which unifies the traditionally distinct objectives of open-vocabulary segmentation - detecting and segmenting object instances based on na…
Point-MoE: Large-Scale Multi-Dataset Training with Mixture-of-Experts for 3D Semantic Segmentation
Xuweiyi Chen, Wentao Zhou, Aruni RoyChowdhury +1
While massively scaling both data and models have become central in NLP and 2D vision, their benefits for 3D point cloud understanding remain limited. We study the initial step of…
Frame In-N-Out: Unbounded Controllable Image-to-Video Generation
Boyang Wang, Xuweiyi Chen, Matheus Gadelha +1
Controllability, temporal coherence, and detail synthesis remain the most critical challenges in video generation. In this paper, we focus on a commonly used yet underexplored cine…
Probing the Mid-level Vision Capabilities of Self-Supervised Learning
Xuweiyi Chen, Markus Marks, Zezhou Cheng
Mid-level vision capabilities - such as generic object localization and 3D geometric understanding - are not only fundamental to human vision but are also crucial for many real-wor…
Semantic-Free Procedural 3D Shapes Are Surprisingly Good Teachers
Xuweiyi Chen, Zezhou Cheng
Self-supervised learning has emerged as a promising approach for acquiring transferable 3D representations from unlabeled 3D point clouds. Unlike 2D images, which are widely access…
Open Vocabulary Monocular 3D Object Detection
Jin Yao, Hao Gu, Xuweiyi Chen +2
We propose and study open-vocabulary monocular 3D detection, a novel task that aims to detect objects of any categores in metric 3D space from a single RGB image. Existing 3D objec…
Multi-Object Hallucination in Vision-Language Models
Xuweiyi Chen, Ziqiao Ma, Xuejun Zhang +5
Large vision language models (LVLMs) often suffer from object hallucination, producing objects not present in the given images. While current benchmarks for object hallucination pr…
3D-GRAND: A Million-Scale Dataset for 3D-LLMs with Better Grounding and Less Hallucination
Jianing Yang, Xuweiyi Chen, Nikhil Madaan +4
The integration of language and 3D perception is crucial for embodied agents and robots that comprehend and interact with the physical world. While large language models (LLMs) hav…
UniCtrl: Improving the Spatiotemporal Consistency of Text-to-Video Diffusion Models via Training-Free Unified Attention Control
Tian Xia, Xuweiyi Chen, Sihan Xu
Video Diffusion Models have been developed for video generation, usually integrating text and image conditioning to enhance control over the generated content. Despite the progress…
LLM-Grounder: Open-Vocabulary 3D Visual Grounding with Large Language Model as an Agent
Jianing Yang, Xuweiyi Chen, Shengyi Qian +4
3D visual grounding is a critical skill for household robots, enabling them to navigate, manipulate objects, and answer questions based on their environment. While existing approac…