484 citations · 1.1k across the 59 of their papers we have counts for
52 papers · 1 filter
Segment Where You Look: Attention as the Interface Between Language Models and Segmenters
Eslam Abdelrahman, Hamza Omar Alkaf, Yuheng Li +5
Vision-language models (VLMs) that segment from language must pass the location of the referent to a pixel decoder. The dominant interface compresses it into the hidden state of a…
VisReflect: Latent Visual Reflection for Fine-Grained Perception in Long Visual Context
Xiaoqian Shen, Mohamed Elhoseiny
Large Vision Language Models (LVLMs) have achieved remarkable success on vision-language tasks, yet fine-grained perception over high-resolution images and long-context videos rema…
Zoom-Zero: Reinforced Coarse-to-Fine Video Understanding via Temporal Zoom-in
Xiaoqian Shen, Min-Hung Chen, Yu-Chiang Frank Wang +2
Grounded video question answering (GVQA) aims to localize relevant temporal segments in videos and generate accurate answers to a given question; however, large video-language mode…
Step-by-step Layered Design Generation
Faizan Farooq Khan, K J Joseph, Koustava Goswami +2
Design generation, in its essence, is a step-by-step process where designers progressively refine and enhance their work through careful modifications. Despite this fundamental cha…
Vgent: Graph-based Retrieval-Reasoning-Augmented Generation For Long Video Understanding
Xiaoqian Shen, Wenxuan Zhang, Jun Chen +1
Understanding and reasoning over long videos pose significant challenges for large video language models (LVLMs) due to the difficulty in processing intensive video tokens beyond c…
ReefNet: A Large-Scale Dataset and Benchmark for Fine-Grained Coral Reef Recognition
Abdulwahab Felemban, Yahia Battach, Faizan Farooq Khan +10
Coral reefs are rapidly declining under anthropogenic pressures (e.g., climate change), creating an urgent need for scalable and automated monitoring. Progress in data-driven coral…
FishNet++: Analyzing the capabilities of Multimodal Large Language Models in marine biology
Faizan Farooq Khan, Yousef Radwan, Eslam Abdelrahman +6
Multimodal large language models (MLLMs) have demonstrated impressive cross-domain capabilities, yet their proficiency in specialized scientific fields like marine biology remains…
Category-level Text-to-Image Retrieval Improved: Bridging the Domain Gap with Diffusion Models and Vision Encoders
Faizan Farooq Khan, Vladan Stojnić, Zakaria Laskar +2
This work explores text-to-image retrieval for queries that specify or describe a semantic category. While vision-and-language models (VLMs) like CLIP offer a straightforward open-…
A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality
Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26
Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…
Neural Catalog: Scaling Species Recognition with Catalog of Life-Augmented Generation
Faizan Farooq Khan, Jun Chen, Youssef Mohamed +2
Open-vocabulary species recognition is a major challenge in computer vision, particularly in ornithology, where new taxa are continually discovered. While benchmarks like CUB-200-2…
4D-Bench: Benchmarking Multi-modal Large Language Models for 4D Object Understanding
Wenxuan Zhu, Bing Li, Cheng Zheng +8
Multimodal Large Language Models (MLLMs) have demonstrated impressive 2D image/video understanding capabilities. However, there are no publicly standardized benchmarks to assess th…
WikiAutoGen: Towards Multi-Modal Wikipedia-Style Article Generation
Zhongyu Yang, Jun Chen, Dannong Xu +5
Knowledge discovery and collection are intelligence-intensive tasks that traditionally require significant human effort to ensure high-quality outputs. Recent research has explored…
3DCoMPaT200: Language-Grounded Compositional Understanding of Parts and Materials of 3D Shapes
Mahmoud Ahmed, Xiang Li, Arpit Prajapati +1
Understanding objects in 3D at the part level is essential for humans and robots to navigate and interact with the environment. Current datasets for part-level 3D object understand…
AVTrustBench: Assessing and Enhancing Reliability and Robustness in Audio-Visual LLMs
Sanjoy Chowdhury, Sayan Nag, Subhrajyoti Dasgupta +4
With the rapid advancement of Multi-modal Large Language Models (MLLMs), several diagnostic benchmarks have recently been developed to assess these models' multi-modal reasoning pr…
Document Haystacks: Vision-Language Reasoning Over Piles of 1000+ Documents
Jun Chen, Dannong Xu, Junjie Fei +2
Large multimodal models (LMMs) have achieved impressive progress in vision-language understanding, yet they face limitations in real-world applications requiring complex reasoning…
LongVU: Spatiotemporal Adaptive Compression for Long Video-Language Understanding
Xiaoqian Shen, Yunyang Xiong, Changsheng Zhao +14
Multimodal Large Language Models (MLLMs) have shown promising progress in understanding and analyzing video content. However, processing long videos remains a significant challenge…
AutoBench-V: Can Large Vision-Language Models Benchmark Themselves?
Han Bao, Yue Huang, Yanbo Wang +7
Large Vision-Language Models (LVLMs) have become essential for advancing the integration of visual and linguistic information. However, the evaluation of LVLMs presents significant…
How Well Can Vision Language Models See Image Details?
Chenhui Gou, Abdulwahab Felemban, Faizan Farooq Khan +4
Large Language Model-based Vision-Language Models (LLM-based VLMs) have demonstrated impressive results in various vision-language understanding tasks. However, how well these VLMs…
Openstory++: A Large-scale Dataset and Benchmark for Instance-aware Open-domain Visual Storytelling
Zilyu Ye, Jinxiu Liu, Ruotian Peng +9
Recent image generation models excel at creating high-quality images from brief captions. However, they fail to maintain consistency of multiple instances across images when encoun…
Goldfish: Vision-Language Understanding of Arbitrarily Long Videos
Kirolos Ataallah, Xiaoqian Shen, Eslam Abdelrahman +6
Most current LLM-based models for video understanding can process videos within minutes. However, they struggle with lengthy videos due to challenges such as "noise and redundancy"…
Meerkat: Audio-Visual Large Language Model for Grounding in Space and Time
Sanjoy Chowdhury, Sayan Nag, Subhrajyoti Dasgupta +4
Leveraging Large Language Models' remarkable proficiency in text-based tasks, recent works on Multi-modal LLMs (MLLMs) extend them to other modalities like vision and audio. Howeve…
InfiniBench: A Benchmark for Large Multi-Modal Models in Long-Form Movies and TV Shows
Kirolos Ataallah, Eslam Abdelrahman, Mahmoud Ahmed +4
Understanding long-form videos, such as movies and TV episodes ranging from tens of minutes to two hours, remains a significant challenge for multi-modal models. Existing benchmark…
VRSBench: A Versatile Vision-Language Benchmark Dataset for Remote Sensing Image Understanding
Xiang Li, Jian Ding, Mohamed Elhoseiny
We introduce a new benchmark designed to advance the development of general-purpose, large-scale vision-language models for remote sensing images. Although several vision-language…
iMotion-LLM: Instruction-Conditioned Trajectory Generation
Abdulwahab Felemban, Nussair Hroub, Jian Ding +4
We introduce iMotion-LLM, a large language model (LLM) integrated with trajectory prediction modules for interactive motion generation. Unlike conventional approaches, it generates…