3 citations · 5 across the 10 of their papers we have counts for
12 papers
CodeActionBench: Evaluating Agentic Code-as-Policy for Embodied Manipulation
Yiheng Lyu, Xueying Jiang, Wenhao Li +2
How well can general-purpose multimodal models turn visual understanding and reasoning into embodied manipulation via executable code? We introduce CodeActionBench, a benchmark of…
3D-Aware VLMs with Implicit and Explicit Geometries
Wenhao Li, Xueying Jiang, Quanhao Qian +4
Despite rapid progress, most existing vision-language models (VLMs) built from 2D visual inputs often struggle when handling various 3D tasks that require fine-grained spatial unde…
From Fixed to Free Cameras: Calibration-Free View-Robust Vision-Language-Action Model
Wenhao Li, Xueying Jiang, Quanhao Qian +4
Real-world robot deployment rarely maintains the training-stage camera setup, where cameras often experience repositioning or remounting depending on actual scenarios. Existing vie…
Towards Camera-Robust 3D Localization: Equation-Anchored Tool-Use for MLLMs
Xueying Jiang, Wenhao Li, Quanhao Qian +4
3D localization in Multimodal Large Language Models (MLLMs), including 3D object detection and 3D visual grounding, is fundamentally limited by camera intrinsic ambiguity: the same…
STS-Mixer: Spatio-Temporal-Spectral Mixer for 4D Point Cloud Video Understanding
Wenhao Li, Xueying Jiang, Gongjie Zhang +3
4D point cloud videos capture rich spatial and temporal dynamics of scenes which possess unique values in various 4D understanding tasks. However, most existing methods work in the…
Exploring 3D Reasoning-Driven Planning: From Implicit Human Intentions to Route-Aware Activity Planning
Xueying Jiang, Wenhao Li, Xiaoqin Zhang +2
3D task planning has attracted increasing attention in human-robot interaction and embodied AI thanks to the recent advances in multimodal learning. However, most existing studies…
Multimodal 3D Reasoning Segmentation with Complex Scenes
Xueying Jiang, Lewei Lu, Ling Shao +1
The recent development in multimodal learning has greatly advanced the research in 3D scene understanding in various real-world tasks such as embodied AI. However, most existing st…
MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
Xueying Jiang, Sheng Jin, Xiaoqin Zhang +2
Monocular 3D object detection aims for precise 3D localization and identification of objects from a single-view image. Despite its recent progress, it often struggles while handlin…
Weakly Supervised Monocular 3D Detection with a Single-View Image
Xueying Jiang, Sheng Jin, Lewei Lu +2
Monocular 3D detection (M3D) aims for precise 3D object localization from a single-view image which usually involves labor-intensive annotation of 3D detection boxes. Weakly superv…
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
Sheng Jin, Xueying Jiang, Jiaxing Huang +2
Inspired by the outstanding zero-shot capability of vision language models (VLMs) in image classification tasks, open-vocabulary object detection has attracted increasing interest…
Domain Generalization via Balancing Training Difficulty and Model Capability
Xueying Jiang, Jiaxing Huang, Sheng Jin +1
Domain generalization (DG) aims to learn domain-generalizable models from one or multiple source domains that can perform well in unseen target domains. Despite its recent progress…
Black-box Unsupervised Domain Adaptation with Bi-directional Atkinson-Shiffrin Memory
Jingyi Zhang, Jiaxing Huang, Xueying Jiang +1
Black-box unsupervised domain adaptation (UDA) learns with source predictions of target data without accessing either source data or source models during training, and it has clear…