activity
20232026
most citedCorrNet+: Sign Language Recognition and Translation via Spatial-Temporal Correlation

2 citations · 4 across the 13 of their papers we have counts for

collaborators

18 papers

math.PR2026

The circle packing and Riemann uniformization embedding of the mated-CRT map converges to Liouville quantum gravity

Nina Holden, Pu Yu

We prove that the mated-CRT map converges to Liouville quantum gravity under circle packing and the Riemann uniformization embedding. The proof is based on our recent work on circl…

cs.LG2026

Physics-Informed Neural Plasticity: PDE Solvers That Reshape Themselves

Chun-Wun Cheng, Bingcheng Hu, Angelica I. Aviles-Rivero

Physics-informed neural PDE solvers adapt their parameters to satisfy governing equations, yet their representational structure typically remains fixed throughout training. This ri…

cs.CV2026

RSure-Agent: Reliable Use of Tool Observations for Remote Sensing Agents

Fuyuan Liu, Nayu Liu, Wenhao Yu +8

Remote sensing agents rely on perception, measurement, and raster analysis tools to solve Earth observation tasks. We refer to their judgments and quantitative results about ground…

cs.CV2026

RegionDet: A Benchmark for Region Detection Beyond Object Instances

Liang Wan, Yuhan Wang, Yupeng Zhang +4

Object detection is a fundamental task in computer vision and has achieved remarkable progress on standard benchmarks by localizing discrete and well-bounded object instances. Howe…

cs.CV2026

ECAD: Expanding Class-Agnostic Detection Beyond Thing-Centric Objectness

Liang Wan, Zixin Ren, Yupeng Zhang +2

Object detection is a fundamental task in visual perception, providing structured region representations for recognition, grounding, reasoning, and interaction. However, existing d…

cs.CV2026

CoLT: Teaching Multi-Modal Models to Think with Chain of Latent Thoughts

Lianyu Hu, Shengqian Qin, Zeqin Liao +4

Chain-of-thought (CoT) reasoning has enabled multi-modal large language models (MLLMs) to tackle complex visual reasoning tasks by generating explicit intermediate reasoning steps…

cs.CV2026

RT-SDGOD: Real-Time Single-Domain Generalized Object Detection

Yupeng Zhang, Fangzhuo Gao, Ruize Han +2

In real-world deployment under strict real-time constraints, weather and imaging variations induce significant distribution shifts, severely degrading detectors. Single-Domain Gene…

cs.CV2026

ExDet: Open-Domain Open-Vocabulary Detection with Cross-modal Extrapolation and Rectification

Yupeng Zhang, Yuzhong Feng, Ruize Han +3

Open-domain open-vocabulary detection (ODOVD) requires detectors to generalize to both novel categories and unseen domains, making it more challenging than open-vocabulary detectio…

cs.CV2026

LV-OSD: Language-Vision-Complementary Open-Set Object Detection

Yupeng Zhang, Ruize Han, Wei Feng +2

Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images. In this work, we propose a…

cs.CV2026

VFMSDG: Unveiling the Power of VFMs for Single-Domain Generalized Object Detection

Yupeng Zhang, Ruize Han, Ningnan Guo +3

Real-world weather, illumination, and imaging variations often induce severe domain shifts, degrading single-source detectors in unseen environments. Existing single-domain general…

cs.CV2026

NoOVD: Novel Category Discovery and Embedding for Open-Vocabulary Object Detection

Yupeng Zhang, Ruize Han, Zhiwei Chen +2

Despite the remarkable progress in open-vocabulary object detection (OVD), a significant gap remains between the training and testing phases. During training, the RPN and RoI heads…

cs.CV2025

ODOV: Benchmark the Open-Domain Open-Vocabulary Object Detection

Yupeng Zhang, Ruize Han, Fangnan Zhou +2

Existing studies typically investigate domain shift and category shift as independent problems, however, in real-world scenarios, the two types of shifts often occur simultaneously…

cs.MA2025★ 1 cited

Knowing When to Critique: Task-Adaptive Metacognitive Regulation for Reliable LLM Reasoning

Xinmeng Hou, Ziting Chang, Zhouquan Lu +6

Large language models (LLMs) reason fluently but do not regulate their reasoning: they apply uniform scrutiny to every input, which leaves them vulnerable to adversarial and counte…

cs.CV2025

Casual Inference via Style Bias Deconfounding for Domain Generalization

Jiaxi Li, Di Lin, Hao Chen +3

Deep neural networks (DNNs) often struggle with out-of-distribution data, limiting their reliability in diverse realworld applications. To address this issue, domain generalization…

cs.CV2024★ 2 cited

CorrNet+: Sign Language Recognition and Translation via Spatial-Temporal Correlation

Lianyu Hu, Wei Feng, Liqing Gao +2

In sign language, the conveyance of human body trajectories predominantly relies upon the coordinated movements of hands and facial expressions across successive frames. Despite th…

cs.LG2024

Elastic Multi-Gradient Descent for Parallel Continual Learning

Fan Lyu, Wei Feng, Yuepan Li +4

The goal of Continual Learning (CL) is to continuously learn from new data streams and accomplish the corresponding tasks. Previously studied CL assumes that data are given in sequ…

cs.CV2023

Long-Tailed Learning as Multi-Objective Optimization

Weiqi Li, Fan Lyu, Fanhua Shang +2

Real-world data is extremely imbalanced and presents a long-tailed distribution, resulting in models that are biased towards classes with sufficient samples and perform poorly on r…

cs.CV2023★ 1 cited

Open Compound Domain Adaptation with Object Style Compensation for Semantic Segmentation

Tingliang Feng, Hao Shi, Xueyang Liu +4

Many methods of semantic image segmentation have borrowed the success of open compound domain adaptation. They minimize the style gap between the images of source and target domain…