activity
20192026
most citedTowards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

25 citations · 69 across the 11 of their papers we have counts for

collaborators

13 papers

cs.RO2026

Geo-VLA: Geometry-Aware Vision-Language-Action Planning via Internalization of Map Semantics

Ran Chen, Jiaxing Ren, Zhikun Zhang +3

Vision-language-action (VLA) models have advanced end-to-end autonomous driving by leveraging foundation models for semantic reasoning and long-tail generalization. However, their…

cs.CL2026

RRM: Experience-Driven Reflective Retrieval Memory for Long-Horizon Multimodal Reasoning

Jingxiang Fan, Junbao Zhuo, Bochao Zou

Existing multimodal long-term memory agents use external memory to overcome the limited context available for long videos. However, most methods emphasize what to store rather than…

cs.CV2026

Video-Only ToM: Enhancing Theory of Mind in Multimodal Large Language Models

Siqi Liu, Xinyang Li, Bochao Zou +3

As large language models (LLMs) continue to advance, there is increasing interest in their ability to infer human mental states and demonstrate a human-like Theory of Mind (ToM). M…

cs.CV2025

ME-TST+: Micro-expression Analysis via Temporal State Transition with ROI Relationship Awareness

Zizheng Guo, Bochao Zou, Junbao Zhuo +1

Micro-expressions (MEs) are regarded as important indicators of an individual's intrinsic emotions, preferences, and tendencies. ME analysis requires spotting of ME intervals withi…

cs.CV2025

AGC-Drive: A Large-Scale Dataset for Real-World Aerial-Ground Collaboration in Driving Scenarios

Yunhao Hou, Bochao Zou, Min Zhang +7

By sharing information across multiple agents, collaborative perception helps autonomous vehicles mitigate occlusions and improve overall perception accuracy. While most previous w…

cs.CV2024

Confusing Pair Correction Based on Category Prototype for Domain Adaptation under Noisy Environments

Churan Zhi, Junbao Zhuo, Shuhui Wang

In this paper, we address unsupervised domain adaptation under noisy environments, which is more challenging and practical than traditional domain adaptation. In this scenario, the…

cs.CV2024★ 8 cited

RhythmFormer: Extracting Patterned rPPG Signals based on Periodic Sparse Attention

Bochao Zou, Zizheng Guo, Jiansheng Chen +3

Remote photoplethysmography (rPPG) is a non-contact method for detecting physiological signals based on facial videos, holding high potential in various applications. Due to the pe…

cs.CV2023

Orthogonal Temporal Interpolation for Zero-Shot Video Recognition

Yan Zhu, Junbao Zhuo, Bin Ma +4

Zero-shot video recognition (ZSVR) is a task that aims to recognize video categories that have not been seen during the model training process. Recently, vision-language models (VL…

cs.CV2021★ 18 cited

Fast Batch Nuclear-norm Maximization and Minimization for Robust Domain Adaptation

Shuhao Cui, Shuhui Wang, Junbao Zhuo +3

Due to the domain discrepancy in visual domain adaptation, the performance of source model degrades when bumping into the high data density near decision boundary in target domain.…

cs.CV2021★ 3 cited

Learning Invariant Representation with Consistency and Diversity for Semi-supervised Source Hypothesis Transfer

Xiaodong Wang, Junbao Zhuo, Shuhao Cui +1

Semi-supervised domain adaptation (SSDA) aims to solve tasks in target domain by utilizing transferable information learned from the available source domain and a few labeled targe…

cs.CV2020★ 14 cited

Gradually Vanishing Bridge for Adversarial Domain Adaptation

Shuhao Cui, Shuhui Wang, Junbao Zhuo +3

In unsupervised domain adaptation, rich domain-specific characteristics bring great challenge to learn domain-invariant representations. However, domain discrepancy is considered t…

cs.CV2020★ 25 cited

Towards Discriminability and Diversity: Batch Nuclear-norm Maximization under Label Insufficient Situations

Shuhao Cui, Shuhui Wang, Junbao Zhuo +3

The learning of the deep networks largely relies on the data with human-annotated labels. In some label insufficient situations, the performance degrades on the decision boundary w…

cs.CV2019★ 1 cited

Unsupervised Open Domain Recognition by Semantic Discrepancy Minimization

Junbao Zhuo, Shuhui Wang, Shuhao Cui +1

We address the unsupervised open domain recognition (UODR) problem, where categories in labeled source domain S is only a subset of those in unlabeled target domain T. The task is…