activity
20242026
collaborators

18 papers

cs.CV2026

TRACE: Temporal Retrieval with Anchored and Convergent Evidence for Long-Horizon Video Understanding

Pengyiang Liu, Junbo Niu, Xiaoyang Hu +4

A long-video answer is evidence-supported only when the frames decoded from the video cover every event the answer depends on. Existing evaluations score final-answer correctness o…

cs.RO2026

CR-Solver: GPU-Accelerated Kinematics Solver for Tendon-driven Continuum Robots

Heqing Yang, Yang Yi, Linqing Zhong +2

Continuum robots provide intrinsic compliance, high dexterity, and safe physical interaction, enabling navigation and manipulation in confined and unstructured environments. Despit…

cs.RO2026

EVA-Client: A Unified Data Collection, Inference, and Deployment Framework for Embodied Policies on Real Robots

Heqing Yang, Yang Yi, Liyao Wang +8

We present EVA-Client, an open-source framework for deployment, data collection, and evaluation of trained manipulation policies on real robots. Sitting between a policy server and…

cs.CV2026

SVCBench: A Streaming Video Counting Benchmark for Spatial-Temporal State Maintenance

Pengyiang Liu, Zhongyue Shi, Hongye Hao +7

Video understanding requires models to continuously track and update world state during playback. Although existing benchmarks have advanced video understanding evaluation across m…

cs.CV2025

EditThinker: Unlocking Iterative Reasoning for Any Image Editor

Hongyu Li, Manyuan Zhang, Dian Zheng +11

Instruction-based image editing has emerged as a prominent research area, which, benefiting from image generation foundation models, have achieved high aesthetic quality, making in…

cs.LG2025

AnyExperts: On-Demand Expert Allocation for Multimodal Language Models with Mixture of Expert

Yuting Gao, Wang Lan, Hengyuan Zhao +3

Multimodal Mixture-of-Experts (MoE) models offer a promising path toward scalable and efficient large vision-language systems. However, existing approaches rely on rigid routing st…

cs.CV2025

MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning

Weikang Shi, Aldrich Yu, Rongyao Fang +11

While Large Language Models (LLMs) have excelled in textual reasoning, they struggle with mathematical domains like geometry that intrinsically rely on visual aids. Existing approa…

cs.CV2025

FLUX-Reason-6M & PRISM-Bench: A Million-Scale Text-to-Image Reasoning Dataset and Comprehensive Benchmark

Rongyao Fang, Aldrich Yu, Chengqi Duan +7

The advancement of open-source text-to-image (T2I) models has been hindered by the absence of large-scale, reasoning-focused datasets and comprehensive evaluation benchmarks, resul…

cs.CL2025

VaccineRAG: Boosting Multimodal Large Language Models' Immunity to Harmful RAG Samples

Qixin Sun, Ziqin Wang, Hengyuan Zhao +6

Retrieval Augmented Generation enhances the response accuracy of Large Language Models (LLMs) by integrating retrieval and generation modules with external knowledge, demonstrating…

cs.RO2025

SkeNa: Learning to Navigate Unseen Environments Based on Abstract Hand-Drawn Maps

Haojun Xu, Jiaqi Xiang, Wu Wei +5

A typical human strategy for giving navigation guidance is to sketch route maps based on the environmental layout. Inspired by this, we introduce Sketch map-based visual Navigation…

cs.RO2025

"Hi AirStar, Guide Me to the Badminton Court."

Ziqin Wang, Jinyu Chen, Xiangyi Zheng +3

Unmanned Aerial Vehicles, operating in environments with relatively few obstacles, offer high maneuverability and full three-dimensional mobility. This allows them to rapidly appro…

cs.CV2025

SOLVE: Synergy of Language-Vision and End-to-End Networks for Autonomous Driving

Xuesong Chen, Linjiang Huang, Tao Ma +3

The integration of Vision-Language Models (VLMs) into autonomous driving systems has shown promise in addressing key challenges such as learning complexity, interpretability, and c…

cs.CV2025

GoT-R1: Unleashing Reasoning Capability of MLLM for Visual Generation with Reinforcement Learning

Chengqi Duan, Rongyao Fang, Yuqing Wang +5

Visual generation models have made remarkable progress in creating realistic images from text prompts, yet struggle with complex prompts that specify multiple objects with precise…

cs.CV2025

GoT: Unleashing Reasoning Capability of Multimodal Large Language Model for Visual Generation and Editing

Rongyao Fang, Chengqi Duan, Kun Wang +9

Current image generation and editing methods primarily process textual prompts as direct inputs without reasoning about visual composition and explicit operations. We present Gener…

cs.CV2025

FlexDrive: Toward Trajectory Flexibility in Driving Scene Reconstruction and Rendering

Jingqiu Zhou, Lue Fan, Linjiang Huang +4

Driving scene reconstruction and rendering have advanced significantly using the 3D Gaussian Splatting. However, most prior research has focused on the rendering quality along a pr…

cs.CV2024

GaussianPainter: Painting Point Cloud into 3D Gaussians with Normal Guidance

Jingqiu Zhou, Lue Fan, Xuesong Chen +3

In this paper, we present GaussianPainter, the first method to paint a point cloud into 3D Gaussians given a reference image. GaussianPainter introduces an innovative feed-forward…

cs.CV2024

FreeEdit: Mask-free Reference-based Image Editing with Multi-modal Instruction

Runze He, Kai Ma, Linjiang Huang +6

Introducing user-specified visual concepts in image editing is highly practical as these concepts convey the user's intent more precisely than text-based descriptions. We propose F…

cs.CV2024

FouriScale: A Frequency Perspective on Training-Free High-Resolution Image Synthesis

Linjiang Huang, Rongyao Fang, Aiping Zhang +4

In this study, we delve into the generation of high-resolution images from pre-trained diffusion models, addressing persistent challenges, such as repetitive patterns and structura…