activity
20202026
most citedImproving Deep Representation Learning via Auxiliary Learnable Target Coding

7 citations · 12 across the 19 of their papers we have counts for

collaborators
Showing 2026Show all

8 papers · 1 filter

cs.CV2026

ControlRadio: Prompt-Driven Controllable Diffusion for Cross-Modal Radio Map Generation

Kangjun Liu, Xiying Pan, Shuhang Zhang +3

Radio maps describe how wireless signals propagate across space and are essential for wireless communication, sensing, and network planning. However, constructing accurate radio ma…

cs.CV2026

RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling

Zheng Fang, Junjie Liu, Kangjun Liu +3

With the emergence of wireless applications in three-dimensional environments, such as the low-altitude airspace and 3D heterogeneous networks, radio map estimation is increasingly…

cs.CV2026

CVSearch: Empowering Multimodal LLMs with Cognitive Visual Search for High-Resolution Image Perception

Liupeng Li, Haoqian Kang, Zhenyu Lu +4

High-resolution (HR) image perception presents a key bottleneck for multimodal large language models (MLLMs). While visual search offers a promising solution, existing methods stru…

cs.CV2026

SegCompass: Exploring Interpretable Alignment with Sparse Autoencoders for Enhanced Reasoning Segmentation

Zhenyu Lu, Liupeng Li, Jinpeng Wang +4

While large language models provide strong compositional reasoning, existing reasoning segmentation pipelines fail to transparently connect this reasoning to visual perception. Cur…

cs.CV2026

C2P-VAR: Continual and Compositional Personalization in Visual Autoregressive Models

Junhao Li, Xinhao Zhong, Yi sun +4

Visual autoregressive (VAR) models have recently emerged as an efficient paradigm for text-to-image generation, yet their personalization capabilities remain largely limited to sta…

cs.CV2026

MARS: Technical Report for the CASTLE Challenge at EgoVis 2026

Haoyu Zhang, Qiaohui Chu, Yisen Feng +4

This report presents MARS, short for Multimodal Agentic Reasoning with Source selection, our system for the CASTLE Challenge at EgoVis 2026. Participants must answer 185 closed-for…

cs.CV2026

Revisiting Uncertainty: On Evidential Learning for Partially Relevant Video Retrieval

Jun Li, Peifeng Lai, Xuhang Lou +5

Partially relevant video retrieval aims to retrieve untrimmed videos using text queries that describe only partial content. However, the inherent asymmetry between brief queries an…

cs.CV2026

DualEraser: Joint Video Object and Effect Removal via Balanced Text-Mask Guidance and Decoupled Locator-Preserver

Yuqing Chen, Lin Liu, Haisu Wu +4

Video object removal frequently struggles to eliminate target objects and their associated complex physical effects (e.g., smoke and light) in real-world scenes. We attribute this…