31 citations · 102 across the 27 of their papers we have counts for
29 papers
Muse Glimmer 30B: An On-Device Agentic Model
Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327
We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…
SetCon: Towards Open-Ended Referring Segmentation via Set-Level Concept Prediction
Zhixiong Zhang, Yizhuo Li, Shuangrui Ding +6
Referring segmentation grounds natural-language queries to pixel-level masks, but extending it to complex scenarios with multiple instances, cross-category groups, or open-ended ta…
WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation
Shuangrui Ding, Xuanlang Dai, Long Xing +14
Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However, most agent benchmarks still…
Demo-ICL: In-Context Learning for Procedural Video Knowledge Acquisition
Yuhao Dong, Shulin Tian, Shuai Liu +6
Despite the growing video understanding capabilities of recent Multimodal Large Language Models (MLLMs), existing video benchmarks primarily assess understanding based on models' s…
SAM 3: Segment Anything with Concepts
Nicolas Carion, Laura Gustafson, Yuan-Ting Hu +35
We present Segment Anything Model (SAM) 3, a unified model that detects, segments, and tracks objects in images and videos based on concept prompts, which we define as either short…
LSVOS 2025 Challenge Report: Recent Advances in Complex Video Object Segmentation
Chang Liu, Henghui Ding, Kaining Ying +46
This report presents an overview of the 7th Large-scale Video Object Segmentation (LSVOS) Challenge held in conjunction with ICCV 2025. Besides the two traditional tracks of LSVOS…
2nd Place Report of MOSEv2 Challenge 2025: Concept Guided Video Object Segmentation via SeC
Zhixiong Zhang, Shuangrui Ding, Xiaoyi Dong +3
Semi-supervised Video Object Segmentation aims to segment a specified target throughout a video sequence, initialized by a first-frame mask. Previous methods rely heavily on appear…
Advancing Complex Video Object Segmentation via Progressive Concept Construction
Zhixiong Zhang, Shuangrui Ding, Xiaoyi Dong +7
We propose Segment Concept (SeC), a concept-driven video object segmentation (VOS) framework that shifts from conventional feature matching to the progressive construction and util…
ScaleCap: Inference-Time Scalable Image Captioning via Dual-Modality Debiasing
Long Xing, Qidong Huang, Xiaoyi Dong +10
This paper presents ScaleCap, an inference-time scalable image captioning strategy that generates comprehensive and detailed image captions. The key challenges of high-quality imag…
SongGen: A Single Stage Auto-regressive Transformer for Text-to-Song Generation
Zihan Liu, Shuangrui Ding, Zhixiong Zhang +6
Text-to-song generation, the task of creating vocals and accompaniment from textual inputs, poses significant challenges due to domain complexity and data scarcity. Existing approa…
Dispider: Enabling Video LLMs with Active Real-Time Interaction via Disentangled Perception, Decision, and Reaction
Rui Qian, Shuangrui Ding, Xiaoyi Dong +5
Active Real-time interaction with video LLMs introduces a new paradigm for human-computer interaction, where the model not only understands user intent but also responds while cont…
MSF: Efficient Diffusion Model Via Multi-Scale Latent Factorize
Haohang Xu, Longyu Chen, Yichen Zhang +2
While diffusion-based generative models have made significant strides in visual content creation, conventional approaches face computational challenges, especially for high-resolut…
OVO-Bench: How Far is Your Video-LLMs from Real-World Online Video Understanding?
Yifei Li, Junbo Niu, Ziyang Miao +12
Temporal Awareness, the ability to reason dynamically based on the timestamp when a question is raised, is the key distinction between offline and online video LLMs. Unlike offline…
InternLM-XComposer2.5-OmniLive: A Comprehensive Multimodal System for Long-term Streaming Video and Audio Interactions
Pan Zhang, Xiaoyi Dong, Yuhang Cao +26
Creating AI systems that can interact with environments over long periods, similar to human cognition, has been a longstanding research goal. Recent advancements in multimodal larg…
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Shuangrui Ding, Rui Qian, Xiaoyi Dong +6
The Segment Anything Model 2 (SAM 2) has emerged as a powerful foundation model for object segmentation in both images and videos, paving the way for various downstream video appli…
Image Compression for Machine and Human Vision with Spatial-Frequency Adaptation
Han Li, Shaohui Li, Shuangrui Ding +5
Image compression for machine and human vision (ICMH) has gained increasing attention in recent years. Existing ICMH methods are limited by high training and storage overheads due…
Rethinking Image-to-Video Adaptation: An Object-centric Perspective
Rui Qian, Shuangrui Ding, Dahua Lin
Image-to-video adaptation seeks to efficiently adapt image models for use in the video domain. Instead of finetuning the entire image backbone, many image-to-video adaptation parad…
Streaming Long Video Understanding with Large Language Models
Rui Qian, Xiaoyi Dong, Pan Zhang +4
This paper presents VideoStreaming, an advanced vision-language large model (VLLM) for video understanding, that capably understands arbitrary-length video with a constant number o…
SongComposer: A Large Language Model for Lyric and Melody Generation in Song Composition
Shuangrui Ding, Zihan Liu, Xiaoyi Dong +6
Creating lyrics and melodies for the vocal track in a symbolic format, known as song composition, demands expert musical knowledge of melody, an advanced understanding of lyrics, a…
Betrayed by Attention: A Simple yet Effective Approach for Self-supervised Video Object Segmentation
Shuangrui Ding, Rui Qian, Haohang Xu +2
In this paper, we propose a simple yet effective approach for self-supervised video object segmentation (VOS). Our key insight is that the inherent structural dependencies present…
InternLM-XComposer: A Vision-Language Large Model for Advanced Text-image Comprehension and Composition
Pan Zhang, Xiaoyi Dong, Bin Wang +18
We propose InternLM-XComposer, a vision-language large model that enables advanced image-text comprehension and composition. The innovative nature of our model is highlighted by th…
Prune Spatio-temporal Tokens by Semantic-aware Temporal Accumulation
Shuangrui Ding, Peisen Zhao, Xiaopeng Zhang +3
Transformers have become the primary backbone of the computer vision community due to their impressive performance. However, the unfriendly computation cost impedes their potential…
Semantics Meets Temporal Correspondence: Self-supervised Object-centric Learning in Videos
Rui Qian, Shuangrui Ding, Xian Liu +1
Self-supervised methods have shown remarkable progress in learning high-level semantics and low-level temporal correspondence. Building on these results, we take one step further a…
Motion-inductive Self-supervised Object Discovery in Videos
Shuangrui Ding, Weidi Xie, Yabo Chen +4
In this paper, we consider the task of unsupervised object discovery in videos. Previous works have shown promising results via processing optical flows to segment objects. However…