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Found 13 papers, 4 papers with code
HAMMR: HierArchical MultiModal React agents for generic VQA
We start from a multimodal ReAct-based system and make it hierarchical by enabling our HAMMR agents to call upon other specialized agents.
How (not) to ensemble LVLMs for VQA
So it is a trivial exercise to create an ensemble with substantial real gains.
Encyclopedic VQA: Visual questions about detailed properties of fine-grained categories
Empirically, we show that our dataset poses a hard challenge for large vision+language models as they perform poorly on our dataset: PaLI [14] is state-of-the-art on OK-VQA [37], yet it only achieves 13. 0% accuracy on our dataset.
Cascaded Video Generation for Videos In-the-Wild
Videos can be created by first outlining a global view of the scene and then adding local details.
INFERNO: Inferring Object-Centric 3D Scene Representations without Supervision
Each object representation defines a localized neural radiance field that is used to generate 2D views of the scene through a differentiable rendering process.
Ranked #6 on
Video Object Tracking
on CATER
Hierarchical Video Generation for Complex Data
Inspired by this we propose a hierarchical model for video generation which follows a coarse to fine approach.
SSW-GAN: Scalable Stage-wise Training of Video GANs
Current state-of-the-art generative models for videos have high computational requirements that impede high resolution generations beyond a few frames.
Supervision Accelerates Pre-training in Contrastive Semi-Supervised Learning of Visual Representations
We investigate a strategy for improving the efficiency of contrastive learning of visual representations by leveraging a small amount of supervised information during pre-training.
Improved Conditional VRNNs for Video Prediction
To address this issue, we propose to increase the expressiveness of the latent distributions and to use higher capacity likelihood models.
Ranked #2 on
Video Prediction
on Cityscapes 128x128
MovieGraphs: Towards Understanding Human-Centric Situations from Videos
Towards this goal, we introduce a novel dataset called MovieGraphs which provides detailed, graph-based annotations of social situations depicted in movie clips.
Annotating Object Instances with a Polygon-RNN
We show that our approach speeds up the annotation process by a factor of 4. 7 across all classes in Cityscapes, while achieving 78. 4% agreement in IoU with original ground-truth, matching the typical agreement between human annotators.
Cross-Modal Scene Networks
Our experiments suggest that our scene representation can help transfer representations across modalities for retrieval.
Learning Aligned Cross-Modal Representations from Weakly Aligned Data
Our experiments suggest that our scene representation can help transfer representations across modalities for retrieval.
