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ShapeR: Robust Conditional 3D Shape Generation from Casual Captures research paper by Meta, 2026

Meta · Multimodal and robotics · Jan 16, 2026 · 27 citations · 25 upvotes · unverified

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What it shows

ShapeR generates high-fidelity 3D shapes from casual image sequences using visual-inertial SLAM, 3D detection, and vision-language models with rectified flow transformer conditioning.

By Yawar Siddiqui, Duncan Frost, Samir Aroudj and 9 more · arXiv 2601.11514 · PDF · Code

UnverifiedHugging Face's summary; not yet checked by hand.

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Other multimodal and robotics papers

Topic
Multimodal and roboticsJan 30, 2023BLIP-2: Bootstrapping Language-Image Pre-training with Frozen Image Encoders and Large Language ModelsBLIP-2 efficiently pre-trains vision-language models using off-the-shelf frozen encoders and decoders, achieving state-of-the-art performance with fewer parameters.Salesforce9,805 citations3 upvotesRead →Multimodal and roboticsJan 28, 2022BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and GenerationBLIP, a Vision-Language Pre-training framework, improves performance across both understanding and generation tasks by bootstrapping captions from noisy web data, achieving state-of-the-art results on image-text retrieval, image captioning, and VQA, and showing strong generalization to video-language tasks.Salesforce7,655 citations5 upvotesRead →Multimodal and roboticsUnverifiedOct 25, 2024GPT-4o System CardGPT-4o is an omnimodal autoregressive model trained to handle text, audio, image, and video inputs, offering high-performance outputs across these modalities, with particular strengths in vision and audio.OpenAI5,388 citations88 upvotesRead →Multimodal and roboticsUnverifiedMar 8, 2024DeepSeek-VL: Towards Real-World Vision-Language UnderstandingDeepSeek-VL is an open-source vision-language model that achieves state-of-the-art performance in real-world applications by combining a hybrid vision encoder with effective pretraining strategies to preserve language model capabilities.DeepSeek939 citations49 upvotesRead →Multimodal and roboticsUnverifiedOct 17, 2024Janus: Decoupling Visual Encoding for Unified Multimodal Understanding and GenerationJanus, an autoregressive framework with separate visual encoding pathways within a unified transformer architecture, enhances performance in unified multimodal understanding and generation.DeepSeek525 citations37 upvotesRead →Multimodal and roboticsUnverifiedSep 26, 2025LongLive: Real-time Interactive Long Video GenerationLongLive is a frame-level autoregressive framework for real-time and interactive long video generation, addressing efficiency and quality challenges through causal attention, KV-recache, streaming long tuning, and short window attention.NVIDIA297 citations191 upvotesRead →
About this paper
Venue
Computer Vision and Pattern Recognition
Citations
27, 4 influential · Semantic Scholar
Upvotes
25 · Hugging Face
Lab
Meta · on Companies · on Acquisitions · on Quarterly · on Paydays · on TechConf

Changes

CitationsNov 9, 2026Influential citations rose from 3 to 4.
CitationsNov 2, 2026Influential citations fell from 4 to 3.
CitationsNov 2, 2026Citations rose from 23 to 27.
CitationsOct 12, 2026Influential citations rose from 2 to 4.
CitationsOct 12, 2026Citations rose from 19 to 23.
CitationsOct 5, 2026Citations rose from 16 to 19.
CitationsSep 25, 2026A first count of 2 influential citations.
CitationsSep 25, 2026A first count of 16 citations.
New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.