1 citations · 5 across the 13 of their papers we have counts for
14 papers
The First EgoCross Challenge at EgoVis 2026: Cross-Domain Egocentric Video Question Answering
Yuqian Fu, Tianwen Qian, Yanjun Li +30
EgoCross is a cross-domain egocentric video question answering benchmark designed to evaluate whether multimodal large language models can generalize beyond common daily-life scena…
Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing
Luca Barsellotti, Martin Sundermeyer, Mattia Segu +5
Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts have reduced the computation…
FINER: MLLMs Hallucinate under Fine-grained Negative Queries
Rui Xiao, Sanghwan Kim, Yongqin Xian +2
Multimodal large language models (MLLMs) struggle with hallucinations, particularly with fine-grained queries, a challenge underrepresented by existing benchmarks that focus on coa…
MOBIUS: Big-to-Mobile Universal Instance Segmentation via Multi-modal Bottleneck Fusion and Calibrated Decoder Pruning
Mattia Segu, Marta Tintore Gazulla, Yongqin Xian +2
Scaling up model size and training data has advanced foundation models for instance-level perception, achieving state-of-the-art in-domain and zero-shot performance across object d…
Omnia de EgoTempo: Benchmarking Temporal Understanding of Multi-Modal LLMs in Egocentric Videos
Chiara Plizzari, Alessio Tonioni, Yongqin Xian +2
Understanding fine-grained temporal dynamics is crucial in egocentric videos, where continuous streams capture frequent, close-up interactions with objects. In this work, we bring…
UIP2P: Unsupervised Instruction-based Image Editing via Edit Reversibility Constraint
Enis Simsar, Alessio Tonioni, Yongqin Xian +2
We propose an unsupervised instruction-based image editing approach that removes the need for ground-truth edited images during training. Existing methods rely on supervised learni…
Active Data Curation Effectively Distills Large-Scale Multimodal Models
Vishaal Udandarao, Nikhil Parthasarathy, Muhammad Ferjad Naeem +6
Knowledge distillation (KD) is the de facto standard for compressing large-scale models into smaller ones. Prior works have explored ever more complex KD strategies involving diffe…
TokenFormer: Rethinking Transformer Scaling with Tokenized Model Parameters
Haiyang Wang, Yue Fan, Muhammad Ferjad Naeem +5
Transformers have become the predominant architecture in foundation models due to their excellent performance across various domains. However, the substantial cost of scaling these…
Toward a Diffusion-Based Generalist for Dense Vision Tasks
Yue Fan, Yongqin Xian, Xiaohua Zhai +4
Building generalized models that can solve many computer vision tasks simultaneously is an intriguing direction. Recent works have shown image itself can be used as a natural inter…
LocCa: Visual Pretraining with Location-aware Captioners
Bo Wan, Michael Tschannen, Yongqin Xian +7
Image captioning has been shown as an effective pretraining method similar to contrastive pretraining. However, the incorporation of location-aware information into visual pretrain…
Text-Conditioned Resampler For Long Form Video Understanding
Bruno Korbar, Yongqin Xian, Alessio Tonioni +2
In this paper we present a text-conditioned video resampler (TCR) module that uses a pre-trained and frozen visual encoder and large language model (LLM) to process long video sequ…
LIME: Localized Image Editing via Attention Regularization in Diffusion Models
Enis Simsar, Alessio Tonioni, Yongqin Xian +2
Diffusion models (DMs) have gained prominence due to their ability to generate high-quality varied images with recent advancements in text-to-image generation. The research focus i…
PALM: Predicting Actions through Language Models
Sanghwan Kim, Daoji Huang, Yongqin Xian +3
Understanding human activity is a crucial yet intricate task in egocentric vision, a field that focuses on capturing visual perspectives from the camera wearer's viewpoint. Traditi…
SILC: Improving Vision Language Pretraining with Self-Distillation
Muhammad Ferjad Naeem, Yongqin Xian, Xiaohua Zhai +3
Image-Text pretraining on web-scale image caption datasets has become the default recipe for open vocabulary classification and retrieval models thanks to the success of CLIP and i…