Parameter-efficient fine-tuning for large models: A comprehensive survey
Large models represent a groundbreaking advancement in multiple application fields,
enabling remarkable achievements across various tasks. However, their unprecedented …
enabling remarkable achievements across various tasks. However, their unprecedented …
Ulip-2: Towards scalable multimodal pre-training for 3d understanding
Recent advancements in multimodal pre-training have shown promising efficacy in 3D
representation learning by aligning multimodal features across 3D shapes their 2D …
representation learning by aligning multimodal features across 3D shapes their 2D …
Point-bind & point-llm: Aligning point cloud with multi-modality for 3d understanding, generation, and instruction following
We introduce Point-Bind, a 3D multi-modality model aligning point clouds with 2D image,
language, audio, and video. Guided by ImageBind, we construct a joint embedding space …
language, audio, and video. Guided by ImageBind, we construct a joint embedding space …
Woodpecker: Hallucination correction for multimodal large language models
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large
Language Models (MLLMs), referring to the phenomenon that the generated text is …
Language Models (MLLMs), referring to the phenomenon that the generated text is …
Binding touch to everything: Learning unified multimodal tactile representations
The ability to associate touch with other modalities has huge implications for humans and
computational systems. However multimodal learning with touch remains challenging due to …
computational systems. However multimodal learning with touch remains challenging due to …
Pointllm: Empowering large language models to understand point clouds
The unprecedented advancements in Large Language Models (LLMs) have created a
profound impact on natural language processing but are yet to fully embrace the realm of 3D …
profound impact on natural language processing but are yet to fully embrace the realm of 3D …
Gpt4point: A unified framework for point-language understanding and generation
Abstract Multimodal Large Language Models (MLLMs) have excelled in 2D image-text
comprehension and image generation but their understanding of the 3D world is notably …
comprehension and image generation but their understanding of the 3D world is notably …
Language embedded 3d gaussians for open-vocabulary scene understanding
Open-vocabulary querying in 3D space is challenging but essential for scene understanding
tasks such as object localization and segmentation. Language-embedded scene …
tasks such as object localization and segmentation. Language-embedded scene …
Visual programming for zero-shot open-vocabulary 3d visual grounding
Abstract 3D Visual Grounding (3DVG) aims at localizing 3D object based on textual
descriptions. Conventional supervised methods for 3DVG often necessitate extensive …
descriptions. Conventional supervised methods for 3DVG often necessitate extensive …
Open3dsg: Open-vocabulary 3d scene graphs from point clouds with queryable objects and open-set relationships
Current approaches for 3D scene graph prediction rely on labeled datasets to train models
for a fixed set of known object classes and relationship categories. We present Open3DSG …
for a fixed set of known object classes and relationship categories. We present Open3DSG …