activity
20232026
most citedMVA2023 Small Object Detection Challenge for Spotting Birds: Dataset, Methods, and Results

20 citations · 32 across the 14 of their papers we have counts for

collaborators

17 papers

cs.SD2026

DeSRPA: Decoupled Speech Role-Playing Agent via Inference-Time Intervention

Wenqiu Tang, Zhen Wan, Takahiro Komamizu +1

While Large Language Models (LLMs) have revolutionized text-based role-playing, creating immersive Speech Role-Playing Agents (SRPAs) requires a seamless bridge between cognitive r…

cs.CV2026

SelectAnyTree: A Promptable Instance Segmentation Model for 3D Forest LiDAR Point Clouds

Trung Thanh Nguyen, Daniel Lusk, Kilian Gerberding +10

Instance segmentation of trees in forest LiDAR point clouds is constrained by label scarcity: A single hectare holds millions of points and hundreds of overlapping tree crowns, mak…

cs.CV2026

ForestMamba: Sparse Mamba with Geometry-guided Queries for 3D Forest Point Cloud Segmentation

Trung Thanh Nguyen, Tuan-Anh Vu, Duc Viet Le +4

Semantic and instance segmentation of terrestrial and drone LiDAR point clouds is emerging as a transformative approach for converting the complex 3D structure of forests into acti…

cs.CV20261 cited

Multi-proposal Collaboration and Multi-task Training for Weakly-supervised Video Moment Retrieval

Bolin Zhang, Chao Yang, Bin Jiang +2

This study focuses on weakly-supervised Video Moment Retrieval (VMR), aiming to identify a moment semantically similar to the given query within an untrimmed video using only video…

cs.CV2026

Static and Dynamic Graph Alignment Network for Temporal Video Grounding

Zhanjie Hu, Bolin Zhang, Jianhua Wang +5

Temporal Video Grounding (TVG) aims to localize temporal moments in an untrimmed video that semantically correspond to given natural language queries. Recently, Graph Convolutional…

cs.CL2026

Facet-Level Persona Control by Trait-Activated Routing with Contrastive SAE for Role-Playing LLMs

Wenqiu Tang, Zhen Wan, Takahiro Komamizu +1

Personality control in Role-Playing Agents (RPAs) is commonly achieved via training-free methods that inject persona descriptions and memory through prompts or retrieval-augmented…