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Found 15 papers, 12 papers with code
Faster Vision Mamba is Rebuilt in Minutes via Merged Token Re-training
Re-training the token-reduced model enhances the performance of Mamba, by effectively rebuilding the key knowledge.
A Stitch in Time Saves Nine: Small VLM is a Precise Guidance for Accelerating Large VLMs
Vision-language models (VLMs) have shown remarkable success across various multi-modal tasks, yet large VLMs encounter significant efficiency challenges due to processing numerous visual tokens.
Ranked #19 on
Visual Question Answering
on MM-Vet
Dynamic Diffusion Transformer
In addition, we design a Spatial-wise Dynamic Token (SDT) strategy to avoid redundant computation at unnecessary spatial locations.
Prioritize Alignment in Dataset Distillation
To achieve this, existing methods use the agent model to extract information from the target dataset and embed it into the distilled dataset.
Is Sora a World Simulator? A Comprehensive Survey on General World Models and Beyond
General world models represent a crucial pathway toward achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications ranging from virtual environments to decision-making systems.
Dynamic Tuning Towards Parameter and Inference Efficiency for ViT Adaptation
Existing parameter-efficient fine-tuning (PEFT) methods have achieved significant success on vision transformers (ViTs) adaptation by improving parameter efficiency.
VSCode: General Visual Salient and Camouflaged Object Detection with 2D Prompt Learning
Salient object detection (SOD) and camouflaged object detection (COD) are related yet distinct binary mapping tasks.
Multi-grained Temporal Prototype Learning for Few-shot Video Object Segmentation
We decompose the query video information into a clip prototype and a memory prototype for capturing local and long-term internal temporal guidance, respectively.
Learning Referring Video Object Segmentation from Weak Annotation
Based on this scheme, we develop a novel RVOS method that exploits weak annotations effectively.
MMBench: Is Your Multi-modal Model an All-around Player?
In response to these challenges, we propose MMBench, a bilingual benchmark for assessing the multi-modal capabilities of VLMs.
Modeling Motion with Multi-Modal Features for Text-Based Video Segmentation
Text-based video segmentation aims to segment the target object in a video based on a describing sentence.
Ranked #10 on
Referring Expression Segmentation
on A2D Sentences
Optical Flow Estimation
Referring Expression Segmentation
+4
Light Field Saliency Detection with Dual Local Graph Learning andReciprocative Guidance
On the other hand, instead of processing the twokinds of data separately, we build a novel dual graph modelto guide the focal stack fusion process using all-focus pat-terns.
Instance-Level Relative Saliency Ranking with Graph Reasoning
Conventional salient object detection models cannot differentiate the importance of different salient objects.
Weakly Supervised Video Salient Object Detection
Significant performance improvement has been achieved for fully-supervised video salient object detection with the pixel-wise labeled training datasets, which are time-consuming and expensive to obtain.
Light Field Saliency Detection With Dual Local Graph Learning and Reciprocative Guidance
In this paper, we model the information fusion within focal stack via graph networks.
