activity
20182026
most citedMore Text, Less Point: Towards 3D Data-Efficient Point-Language Understanding

1 citations · 3 across the 12 of their papers we have counts for

collaborators

15 papers

cs.AI2026

Value-Guided Repulsion for Offline Reinforcement Learning

Yixue Hao, Jiahao Zhang, Jiesong Lian +5

Drifting models have emerged as a highly efficient and stable paradigm for policy design in offline reinforcement learning (RL). However, standard drift policies determine repulsio…

cs.CV2026

CoDy: Codec Dynamics as Complementary Priors for Unsupervised Temporal Action Localization

Tianyu Yan, Qingyi Yang, Qin Yang +5

Unsupervised temporal action localization (UTAL) aims to identify action categories and localize their temporal boundaries without annotation supervision. Existing methods typicall…

cs.CV2026

DepthTile: Depth-Guided Existing-Image Self-Tiling with Input-Side Tileability Assessment

Rui Wang, Xi Chen, Hui Dai +4

Existing-image self-tiling aims to transform a given image into a seamlessly repeatable tile while preserving its original semantics and local details. This task requires weak edit…

cs.CV2026

Counting Beyond Instances: A Benchmark for Group-Individual Object Counting

Rui Wang, Junyi Huang, Jiahui Li +4

Visual counting is commonly formulated at the instance level, aiming to estimate how many objects of a queried category appear in an image. However, real-world counting often invol…

cs.CV2026

SARA: Semantically Adaptive Relational Alignment for Video Diffusion Models

Jiesong Lian, Zixiang Zhou, Ruizhe Zhong +6

Recent video diffusion models (VDMs) synthesize visually convincing clips, yet still drop entities, mis-bind attributes, and weaken the interactions specified in the prompt. Repres…

cs.CL2024★ 1 cited

Natural Language Fine-Tuning

Jia Liu, Yue Wang, Zhiqi Lin +3

Large language model fine-tuning techniques typically depend on extensive labeled data, external guidance, and feedback, such as human alignment, scalar rewards, and demonstration.…

cs.CV2024

Fancy123: One Image to High-Quality 3D Mesh Generation via Plug-and-Play Deformation

Qiao Yu, Xianzhi Li, Yuan Tang +4

Generating 3D meshes from a single image is an important but ill-posed task. Existing methods mainly adopt 2D multiview diffusion models to generate intermediate multiview images,…

cs.AI2024

DCMAC: Demand-aware Customized Multi-Agent Communication via Upper Bound Training

Dongkun Huo, Huateng Zhang, Yixue Hao +4

Efficient communication can enhance the overall performance of collaborative multi-agent reinforcement learning. A common approach is to share observations through full communicati…

cs.CV2024★ 1 cited

More Text, Less Point: Towards 3D Data-Efficient Point-Language Understanding

Yuan Tang, Xu Han, Xianzhi Li +5

Enabling Large Language Models (LLMs) to comprehend the 3D physical world remains a significant challenge. Due to the lack of large-scale 3D-text pair datasets, the success of LLMs…

cs.LG2024

Multimodal Physiological Signals Representation Learning via Multiscale Contrasting for Depression Recognition

Kai Shao, Rui Wang, Yixue Hao +3

Depression recognition based on physiological signals such as functional near-infrared spectroscopy (fNIRS) and electroencephalogram (EEG) has made considerable progress. However,…

cs.CV2024

PointDreamer: Zero-shot 3D Textured Mesh Reconstruction from Colored Point Cloud

Qiao Yu, Xianzhi Li, Yuan Tang +4

Faithfully reconstructing textured meshes is crucial for many applications. Compared to text or image modalities, leveraging 3D colored point clouds as input (colored-PC-to-mesh) o…

cs.CV2024★ 1 cited

MiniGPT-3D: Efficiently Aligning 3D Point Clouds with Large Language Models using 2D Priors

Yuan Tang, Xu Han, Xianzhi Li +4

Large 2D vision-language models (2D-LLMs) have gained significant attention by bridging Large Language Models (LLMs) with images using a simple projector. Inspired by their success…

cs.CV2024

PDF: A Probability-Driven Framework for Open World 3D Point Cloud Semantic Segmentation

Jinfeng Xu, Siyuan Yang, Xianzhi Li +4

Existing point cloud semantic segmentation networks cannot identify unknown classes and update their knowledge, due to a closed-set and static perspective of the real world, which…

cs.CV2022

CasFusionNet: A Cascaded Network for Point Cloud Semantic Scene Completion by Dense Feature Fusion

Jinfeng Xu, Xianzhi Li, Yuan Tang +4

Semantic scene completion (SSC) aims to complete a partial 3D scene and predict its semantics simultaneously. Most existing works adopt the voxel representations, thus suffering fr…

cs.NI2018

Label-less Learning for Traffic Control in an Edge Network

Min Chen, Yixue Hao, Kai Lin +2

With the development of intelligent applications (e.g., self-driving, real-time emotion recognition, etc), there are higher requirements for the cloud intelligence. However, cloud…