activity
20242026
collaborators

14 papers

cs.CV2026

LIFT: Layout-In-Future Video Generation under Large Viewpoint Change via On-Policy Self-Distillation

Shengxiang Ji, Boyang Wang, Haiyang Xu +9

We introduce LIFT, a unified image-to-video generation framework that complements camera control with Layout-In-FuTure control, enabling users to specify what should appear in a fu…

cs.RO2026

Foresight: Failure Detection for Long-Horizon Robotic Manipulation with Action-Conditioned World Model Latents

Haoran Zhang, Yifu Lu, Boyang Wang +5

Long-horizon tasks are common in real-world robotic deployments, yet failure detection for such tasks remains underexplored. Detecting failures in long-horizon robotic tasks is par…

cs.CV2026

VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving

Jin Yao, Dhruva Dixith Kurra, Tom Lampo +3

Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D world around them. Existing ap…

cs.CV2026

OmniShotCut: Holistic Relational Shot Boundary Detection with Shot-Query Transformer

Boyang Wang, Guangyi Xu, Jiahui Zhang +2

Shot Boundary Detection (SBD) aims to automatically identify shot changes and divide a video into coherent shots. While SBD was widely studied in the literature, existing methods o…

cs.CV2026

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…

cs.CV2026

LabelAny3D: Label Any Object 3D in the Wild

Jin Yao, Radowan Mahmud Redoy, Sebastian Elbaum +2

Detecting objects in 3D space from monocular input is crucial for applications ranging from robotics to scene understanding. Despite advanced performance in the indoor and autonomo…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2025

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CV2024

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…

cs.CL2024

Machine Unlearning of Pre-trained Large Language Models

Jin Yao, Eli Chien, Minxin Du +4

This study investigates the concept of the `right to be forgotten' within the context of large language models (LLMs). We explore machine unlearning as a pivotal solution, with a f…