65 citations · 157 across the 36 of their papers we have counts for
37 papers
DDA-Thinker: Decoupled Dual-Atomic Reinforcement Learning for Reasoning-Driven Image Editing
Hanqing Yang, Qiang Zhou, Yongchao Du +6
Recent image editing models have achieved strong visual fidelity but often struggle with tasks requiring complex reasoning. To investigate and enhance the reasoning-grounded planni…
AdaSpark: Adaptive Sparsity for Efficient Long-Video Understanding
Handong Li, Zikang Liu, Longteng Guo +10
Processing long-form videos with Video Large Language Models (Video-LLMs) is computationally prohibitive. Current efficiency methods often compromise fine-grained perception throug…
GIFT: Global Irreplaceability Frame Targeting for Efficient Video Understanding
Junpeng Ma, Sashuai Zhou, Guanghao Li +9
Video Large Language Models (VLMs) have achieved remarkable success in video understanding, but the significant computational cost from processing dense frames severely limits thei…
SpatialReward: Verifiable Spatial Reward Modeling for Fine-Grained Spatial Consistency in Text-to-Image Generation
Sashuai Zhou, Qiang Zhou, Junpeng Ma +9
Recent advances in text-to-image (T2I) generation via reinforcement learning (RL) have benefited from reward models that assess semantic alignment and visual quality. However, most…
Contribution-aware Token Compression for Efficient Video Understanding via Reinforcement Learning
Yinchao Ma, Qiang Zhou, Zhibin Wang +4
Video large language models have demonstrated remarkable capabilities in video understanding tasks. However, the redundancy of video tokens introduces significant computational ove…
StreamKV: Streaming Video Question-Answering with Segment-based KV Cache Retrieval and Compression
Yilong Chen, Xiang Bai, Zhibin Wang +4
Video Large Language Models (Video-LLMs) have demonstrated significant potential in the areas of video captioning, search, and summarization. However, current Video-LLMs still face…
GMoPE:A Prompt-Expert Mixture Framework for Graph Foundation Models
Zhibin Wang, Zhixing Zhang, Shuqi Wang +2
Graph Neural Networks (GNNs) have demonstrated impressive performance on task-specific benchmarks, yet their ability to generalize across diverse domains and tasks remains limited.…
BLM: A Boundless Large Model for Cross-Space, Cross-Task, and Cross-Embodiment Learning
Wentao Tan, Bowen Wang, Heng Zhi +15
Multimodal large language models (MLLMs) have advanced vision-language reasoning and are increasingly deployed in embodied agents. However, significant limitations remain: MLLMs ge…
ReWatch-R1: Boosting Complex Video Reasoning in Large Vision-Language Models through Agentic Data Synthesis
Congzhi Zhang, Zhibin Wang, Yinchao Ma +5
While Reinforcement Learning with Verifiable Reward (RLVR) significantly advances image reasoning in Large Vision-Language Models (LVLMs), its application to complex video reasonin…
MMG-Vid: Maximizing Marginal Gains at Segment-level and Token-level for Efficient Video LLMs
Junpeng Ma, Qizhe Zhang, Ming Lu +4
Video Large Language Models (VLLMs) excel in video understanding, but their excessive visual tokens pose a significant computational challenge for real-world applications. Current…
Multimodal LLM Enhanced Cross-lingual Cross-modal Retrieval
Yabing Wang, Le Wang, Qiang Zhou +4
Cross-lingual cross-modal retrieval (CCR) aims to retrieve visually relevant content based on non-English queries, without relying on human-labeled cross-modal data pairs during tr…
I2EBench: A Comprehensive Benchmark for Instruction-based Image Editing
Yiwei Ma, Jiayi Ji, Ke Ye +6
Significant progress has been made in the field of Instruction-based Image Editing (IIE). However, evaluating these models poses a significant challenge. A crucial requirement in t…
INF-LLaVA: Dual-perspective Perception for High-Resolution Multimodal Large Language Model
Yiwei Ma, Zhibin Wang, Xiaoshuai Sun +4
With advancements in data availability and computing resources, Multimodal Large Language Models (MLLMs) have showcased capabilities across various fields. However, the quadratic c…
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
Shaofeng Zhang, Jinfa Huang, Qiang Zhou +4
Image outpainting aims to generate the content of an input sub-image beyond its original boundaries. It is an important task in content generation yet remains an open problem for g…
InfMLLM: A Unified Framework for Visual-Language Tasks
Qiang Zhou, Zhibin Wang, Wei Chu +3
Large language models (LLMs) have proven their remarkable versatility in handling a comprehensive range of language-centric applications. To expand LLMs' capabilities to a broader…
Data Pruning via Moving-one-Sample-out
Haoru Tan, Sitong Wu, Fei Du +4
In this paper, we propose a novel data-pruning approach called moving-one-sample-out (MoSo), which aims to identify and remove the least informative samples from the training set.…
ICPC: Instance-Conditioned Prompting with Contrastive Learning for Semantic Segmentation
Chaohui Yu, Qiang Zhou, Zhibin Wang +1
Modern supervised semantic segmentation methods are usually finetuned based on the supervised or self-supervised models pre-trained on ImageNet. Recent work shows that transferring…
ES-MVSNet: Efficient Framework for End-to-end Self-supervised Multi-View Stereo
Qiang Zhou, Chaohui Yu, Jingliang Li +3
Compared to the multi-stage self-supervised multi-view stereo (MVS) method, the end-to-end (E2E) approach has received more attention due to its concise and efficient training pipe…
RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension
Qiang Zhou, Chaohui Yu, Shaofeng Zhang +3
In this work, we investigate extending the comprehension of Multi-modal Large Language Models (MLLMs) to regional objects. To this end, we propose to extract features corresponding…
Improved Neural Radiance Fields Using Pseudo-depth and Fusion
Jingliang Li, Qiang Zhou, Chaohui Yu +4
Since the advent of Neural Radiance Fields, novel view synthesis has received tremendous attention. The existing approach for the generalization of radiance field reconstruction pr…
Points-to-3D: Bridging the Gap between Sparse Points and Shape-Controllable Text-to-3D Generation
Chaohui Yu, Qiang Zhou, Jingliang Li +3
Text-to-3D generation has recently garnered significant attention, fueled by 2D diffusion models trained on billions of image-text pairs. Existing methods primarily rely on score d…
SwinRDM: Integrate SwinRNN with Diffusion Model towards High-Resolution and High-Quality Weather Forecasting
Lei Chen, Fei Du, Yuan Hu +2
Data-driven medium-range weather forecasting has attracted much attention in recent years. However, the forecasting accuracy at high resolution is unsatisfactory currently. Pursuin…
UniNeXt: Exploring A Unified Architecture for Vision Recognition
Fangjian Lin, Jianlong Yuan, Sitong Wu +2
Vision Transformers have shown great potential in computer vision tasks. Most recent works have focused on elaborating the spatial token mixer for performance gains. However, we ob…
D2Q-DETR: Decoupling and Dynamic Queries for Oriented Object Detection with Transformers
Qiang Zhou, Chaohui Yu, Zhibin Wang +1
Despite the promising results, existing oriented object detection methods usually involve heuristically designed rules, e.g., RRoI generation, rotated NMS. In this paper, we propos…