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- VBench: Comprehensive Benchmark Suite for Video Generative Models2,062
VBench is a comprehensive benchmark suite that dissects “video generation quality” into specific, hierarchical, and disentangled dimensions, each with tailored prompts and evaluation methods, and investi-gate the gaps between video and image generation models.
- InternVideo: General Video Foundation Models via Generative and Discriminative Learning584
Without bells and whistles, InternVideo achieves state-of-the-art performance on 39 video datasets from extensive tasks including video action recognition/detection, video-language alignment, and open-world video applications.
- InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation557
A scalable approach to autonomously build a high-quality video-text dataset with large language models (LLM), thereby showcasing its efficacy in learning video-language representation at scale and introducing ViCLIP, a video- Text representation learning model based on ViT-L.
- LaVie: High-Quality Video Generation with Cascaded Latent Diffusion Models426
The incorporation of simple temporal self-attentions, coupled with rotary positional encoding, adequately captures the temporal correlations inherent in video data and proves that the process of joint image-video fine-tuning plays a pivotal role in producing high-quality and creative outcomes.
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- SEINE: Short-to-Long Video Diffusion Model for Generative Transition and Prediction267
This paper proposes a random-mask video diffusion model to automatically generate transitions based on textual descriptions that generates transition videos that ensure coherence and visual quality and validate the effectiveness of the approach over existing methods for generative transition and prediction.
- InternGPT: Solving Vision-Centric Tasks by Interacting with ChatGPT Beyond Language113
By incorporating pointing instructions, the proposed iGPT significantly improves the efficiency of communication between users and chatbots, as well as the accuracy of chatbots in vision-centric tasks, especially in complicated visual scenarios where the number of objects is greater than 2.
- MM-Pyramid: Multimodal Pyramid Attentional Network for Audio-Visual Event Localization and Video Parsing98
A Multimodal Pyramid Attentional Network (MM-Pyramid) for event localization and an adaptive semantic fusion module, which leverages a unit-level attention block and a selective fusion block to integrate pyramid features interactively, are presented.
- Modality-aware Contrastive Instance Learning with Self-Distillation for Weakly-Supervised Audio-Visual Violence Detection80
This paper proposes a modality-aware contrastive instance learning with self-distillation (MACIL-SD) strategy, which leverages a lightweight two-stream network to generate audio and visual bags, in which unimodal background, violent, and normal instances are clustered into semi-bags in an unsupervised way.
- InternVideo-Ego4D: A Pack of Champion Solutions to Ego4D Challenges62
In these five tasks, the performance of InternVideo-Ego4D comprehensively surpasses the baseline methods and the champions of CVPR2022, demonstrating the powerful representation ability of Intern video as a video foundation model.
- OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text60
This paper introduces OmniCorpus, a 10 billion-scale image-text interleaved dataset that has 15 times larger scales while maintaining good data quality and is more flexible, easily degradable from an image-text interleaved format to pure text corpus and image-text pairs.
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- VRBench: A Benchmark for Multi-Step Reasoning in Long Narrative Videos31
This work presents VRBench, the first long narrative video benchmark crafted for evaluating large models' multi-step reasoning capabilities, and proposes a progress-level LLM-guided scoring metric to evaluate the quality of the reasoning chain from multiple dimensions comprehensively.
- Long-Term Rhythmic Video Soundtracker31
Long-Term Rhythmic Video Soundtracker (LORIS), a novel framework to synthesize long-term conditional waveforms consisting of a latent conditional diffusion probabilistic model to perform waveform synthesis, is presented.
- Intern-S1-Pro: Scientific Multimodal Foundation Model at Trillion Scale23
This work introduces Intern-S1-Pro, the first one-trillion-parameter scientific multimodal foundation model, which further fortifies the fusion of general and specialized intelligence, working as a Specializable Generalist, demonstrating its position in the top tier of open-source models for general capabilities.
- MPN: Multimodal Parallel Network for Audio-Visual Event Localization21
A Multimodal Parallel Network (MPN), which can perceive global semantics and unmixed local information parallelly, and achieves the state-of-the-art performance both in fully supervised and weakly supervised settings on the Audio-Visual Event (AVE) dataset.
- Exploring Logical Reasoning for Referring Expression Comprehension16
A logic-guided approach to explore logical knowledge for referring expression comprehension in a hierarchical modular-based framework to extract fine-grained cues in visual and textual domains and perform logical reasoning over them with explicit logical expressions to regularize the matching process without extra parameters.
- Learning Music-Dance Representations Through Explicit-Implicit Rhythm Synchronization12
MuDaR is introduced, a novel Music-Dance Representation learning framework to perform the synchronization of music and dance rhythms both in explicit and implicit ways, and outperforms other self-supervised methods by a large margin.
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Publication data from OpenAlex; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-16. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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